{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 说明\n",
    "本篇博客采用的卷积神经网络模型是Lecun于2011年发表的论文：\n",
    "[Traffic Sign Recognition with Multi-Scale Convolutional Networks](https://scholar.google.com/scholar_url?url=http://ieeexplore.ieee.org/abstract/document/6033589/&hl=zh-CN&sa=T&oi=gsb&ct=res&cd=0&ei=3rrqWtr1IsSyyASpkrLgDA&scisig=AAGBfm1qTtsdXG41K740eWaSoOr0-BKhoQ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape: (34799, 32, 32, 3)\n",
      "y_train shape: (34799,)\n",
      "X_test shape: (12630, 32, 32, 3)\n",
      "y_test shape: (12630,)\n"
     ]
    }
   ],
   "source": [
    "# Load data\n",
    "import pickle\n",
    "training_file = 'data/train.p'\n",
    "testing_file = 'data/test.p'\n",
    "\n",
    "with open(training_file,mode='rb') as f:\n",
    "    train = pickle.load(f)\n",
    "with open(testing_file,mode='rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "X_train,y_train = train['features'],train['labels']\n",
    "X_test,y_test = test['features'],test['labels']\n",
    "\n",
    "print('X_train shape:',X_train.shape)\n",
    "print('y_train shape:',y_train.shape)\n",
    "print('X_test shape:',X_test.shape)\n",
    "print('y_test shape:',y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of classes:43\n",
      "Number of training examples = 34799\n",
      "Number of testing examples = 12630\n",
      "Image data shape= (32, 32, 3)\n",
      "Number of classes = 43\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "n_train = len(X_train)\n",
    "n_test = len(X_test)\n",
    "\n",
    "_,IMG_HEIGHT,IMG_WIDTH,IMG_DEPTH = X_train.shape\n",
    "image_shape = (IMG_HEIGHT,IMG_WIDTH,IMG_DEPTH)\n",
    "\n",
    "with open('data/signnames.csv','r') as sign_name:\n",
    "    reader = csv.reader(sign_name)\n",
    "    sign_names = list(reader)\n",
    "\n",
    "sign_names = sign_names[1::]\n",
    "NUM_CLASSES = len(sign_names)\n",
    "print('Total number of classes:{}'.format(NUM_CLASSES))\n",
    "\n",
    "n_classes = len(np.unique(y_train))\n",
    "assert (NUM_CLASSES== n_classes) ,'1 or more class(es) not represented in training set'\n",
    "\n",
    "n_test = len(y_test)\n",
    "\n",
    "print('Number of training examples =',n_train)\n",
    "print('Number of testing examples =',n_test)\n",
    "print('Image data shape=',image_shape)\n",
    "print('Number of classes =',n_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ij3uRwF2/B2uu4KkiXUeLb1bDy5d28uyVPJONNHgh4HWer/21ZhneZVA6aUW00bYJXtqldL7PExtb0bDXBsET0ZoWdQLVuxT2fryKVsQdd+yHvOc//Fcq3Xv2CSiTOveybf8hlW40HbMOpw5W6DsusFTutEFh+qHZ7kCZ73j7d0He3rYWTi8bAaiIyLMnXlLpoROxPXHGpjUtyZpYpyzDz/VMHbobKDjt9lG8aiPQO/42UsvQNKHVmdTXcYTN0ZnXvoj/6tFw6t6ua6FtGtAQochwiR/0eyo9exH7ff8AzT/OtvQ9T+6chDLBEfYvJloU3XUWpaV5NC4ZNner9HvufgDKzExoEf3ew3dBmbSLyvQXhrpdFp3v/9pKH/Lmeka8feMhKFNvoQi8Na3NMaan0Hzk/JmzkPfEoq5Xcxte+5CgEP0Gk9UZb8JB50rxtl67f2xye7YbludhlDqfs8uwNaq49H3O/mh3e29a24VZRIJZExLH2iAzhgFJvYbXdupkbyYJzuccYyy7X2ZOQyUZXmsw0nMoOvPTM/kKprFK73nAWYgTa3p1lZfSwjp2iEgw7eet54XzoFKavM0aWsD3b6KMdy3v2fSKr2+e1cbe/TrfODGh9/J77roJvz93TItEj712gntTsY7mGGuruhWeO/IilOlMoRHVatDPCcPlBSgz4/RgOdLz9pkzJ6DMZuAvV4QQQgghhBBSAXy5IoQQQgghhJAK4MsVIYQQQgghhFTANdVceYCuxjksOvaC+przoW7gX+f7bHBc/wzrlR0C9mQYNaPhqDsaiJrJq9WwjBdcuTRniQsnwKs9IyyCwfGGTiOUzjnvNNF5jmRGcieY6mY0Vt7Z3mgOn5fO2feqOPKJz0DehSe15ipztEW5EzjRtvnYqbZ3Vrs0Y9hrt8IK30RAmHDjoTuxnk99DvK6X3xZpWfu+g4oc9uBgyp93NPG5M5ZbRNIdW3+FJQZDFDTkgQ99hNHazSzfQrycmgs56x/xHoWuT6XPXICFAent9KaPVO+SSHhFbK+joEMdx84pNKJEwB5Pe9BnpgmLduo2SknsP0mE6PNKFFHd2YJg/H2tmvt1J49GOj35j0HIO+Otzyo0jun8HN2Dcqa2AZeNNBDd9+ni2xg/73twsuQd/TEp1S6N8CxcWED5+jCktawzV84CmW6C6h9a07qft/TxP4cnz8PeRPL+n6GS2tQpioKb12GPEf/42xqVpftaSfdQOrm+6Iz12OJa3Wa2f0ZtSKp82yRmb3QXSPM/SWOhtZbp0rzzDBqO/tOxP15ONbrqacj8jTtUM4Jgu3qzkw9bVBaEZHS0QjnhekHp6+qJHd0bVlN1z2xol3xdXve85RlEyG1pXD2zEEP90Nbz3oL17fNPBU5Ej2ZMmPhlm3TUKazhnnrNf25ofcwIzjXsmg0Xn1nnLVx/p1Y0uvii4u4Lq+cwoD2eWK0/jnqiIuxM49yveb2c3zm2Qz85YoQQgghhBBCKoAvV4QQQgghhBBSAXy5IoQQQgghhJAK4MsVIYQQQgghhFTAtTW0cIPTGYMJR7BvjRtERKI1c3AMEUpH6mdFil6w3GiD3IlIMKYBVqwqgsYUIiITdS3ynHTMKhrGKKHhXCckeH+5CcBcOOpfLxBe18ZgHTui0xSFfpnJS50ghZ5oMEQrNoYiEl1rETM2HIFpVVz4MgrMZ/bcoL9/Pwp2V05gQLuir9vA0dNL3RGB2rvzxNzOVJB+X4tHZzoY3HXx4mnISwc6YF/3yJNQZvaND6r0ShuD/J28cA7yuhu6XO6IubfvxeCDrZq+ac+kxQsGOhrqNg9OgMIQUWQ7HOjJkDlBhFNnLsSoOzUfY2DjKmm3ZyGv1dL9nDew7ktzFyEvTXXbnHHWu3PraK6w25h91BpYp/l17Jv73vkGlX7T4fugzPYOBsdNgw4gPVx9DsqsmbHvjbOaExA51HUb1Du7oMxdb7sH8m5/iw5SPPf0HJQ5uXwc8p544c9U+twFbKfWJLbBnTO6j290ykysoZg79LTxRXI1PQO8oPd2r/cjBkNOaRY9G6hWxA92aldPb31t1XAe1+q6PUOBi3Uc4JqX59ogpBhjnRJT98QLYuyYTlhDi1jDZ41mB++lUdcGM6GOhjN9x5jCLAfuPps4Ayg15kOpYwqROFGgS/PY6bVdlXjBjdM6GidYotNWRf7qzyBuHGqzjw3WHGMaZw+p17TZ0GbMMkTwWSJ4sapXllV66egzUGbtFO7t6YRe98tJHGcjQWOzmqlV2sA9up/j/LvY19ead+boyDHQKHrmOWyAdWo30MxpsqPrNe46Qbw3AX+5IoQQQgghhJAK4MsVIYQQQgghhFQAX64IIYQQQgghpAL4ckUIIYQQQgghFbD1hhZGPJl75hVuCGpjkuBc2w1LDRHDUQ6YWYWniNSNADJzBPOeEcVEXV+/5ZhspEbIGMcowI5OIwQjIHWNMFJ8f05MudJpg5Ej7Lf95xqNONHWfbOKvz5eG1SFZ87RH+tI3VmG0cpr07shrxhpweXQMWlpZJhni5Wo0ZSlixjF/dxZbVowfvlZKDNeQ1G2FfqWGwtQZv3IV1R638FDUGbBEQfXd+zT3++NaccUptHWAtPRAO+3cAStqTGKKR0xcpI2Ia9u5ufIERWPc8zLavqe662r+3eq1b5jxjHWecUY+3jaEQ3nxjSgu7YMZZo1bPeVvm6HYoT9/sB7vgfy3vDGN6n0RI7rzdrTX4W8xtIRXc+TWGZlw7RBiqYzmSO0l6Fuq4kmirKT294IefnOW1V69w33Q5mZm/dAXnfipEq/+PCnoUxsYB12J1r4PlzH/ny6j/Nh3bgWpTVnPa+K4Bi+mL0idfZiz8whhM3MI7zfRqbr0KmhUD2L+Lmyp40pxn1cpxLHpEmMOUXq1DuIrlN0nhk8062Y6zGd5Lin5gP8XFbTfR6auG61p7BdRjU9Z8bOdl06bWC3Y8+wIyY47uzzgGdQVCVNp29qJs/rP8dDDBonOj5GA2e52Rjqxlof4lhMumhyMTM1pb/PMwPzDGVsuSHuH+WKNsJZfhGfGxZeOgN5tR13qHR+wwEok006BijmmSdxngsT56Fn0uy1k95y7jy/xXZLpXviGNo4Jjf1TNe95bwPbAb+ckUIIYQQQgghFcCXK0IIIYQQQgipAL5cEUIIIYQQQkgFXFPNlXfGOjdBw7wAdrUMz0Um9lCpF/zP+b6aOXteOEEn246GZLJlzsM7ce+8Y+1JrgOXjUvnrK05l5w4eic3oJ05q5yPnMBtjt6gZdrT02V5IVGHpm/6jr7Kk75ZrZQXuDk4+pvE1D2EqzdcR85B3qE52585OpTGgRsgL919UKUj6PxEvLiJZaHLDbo4Fy6ewaClvUWtlRoePwJlvPjLE7fq4K6DRQx+2p3Tec3Odihzz60YbPXI2VP62s4YGzjBOftGO5U6moTgBL2tNXQw0HLkBBV0xl2zo8+0y6ALZTytX5LpNSL1NIoVcmYBgwEXgw2VntqGbVzvoM5sY1UH5x3n2FbrDWetbut2+O4HDkKZt77tAcirjfS86T/xcfy+55/GvERrQZrbb4cyB15/p0pnN2OZ6KyB5ekXVLp7FPVcZ57DPOk/pZKzt+B63nn3WyDvzXf9XV1PR6zx/JEvQV69qxeK7gj3whPL2O9ptl+l4wYGA62KxNMSmailpaN3Cu7ctsGH8fuajrZ42uiGEkevOh5uQF4xtjoXRxPtBBpNzbpRn0I9rtS05qN01i2rrxIRGRsNZNnHfSd3tGGlCaSejPFzUuL6Njm9V6U3BANVdx3dV1mYMexppzytuGljLwhupTjBYxvmWcILVp04vz2URjs17mG7nFzFAOynVuZVemkZy9zWRL3ovo4eQ3HbDJRZ7a5BXhzpsdDKnQDzL59Q6Ze+8DkoU6wsQd7+tl6D1h393yBB/WhmnjsbNXzOXl3A55vxhm67Ro5juOHE+R2aZ/vYcHSRTpBrK8OKQ/y+zcBfrgghhBBCCCGkAvhyRQghhBBCCCEVwJcrQgghhBBCCKkAvlwRQgghhBBCSAVcU0OLsROdzhpK1ByxauKYHViFfoxeED/EBgiuZfi5yTYKC9sm4FlIUMg40UYRX5pqQWKrgSK+7du0GLbhGGoUjqFFbgKerq+i+HBtaR7yxAhRG847duYE/7P9MHL0q8F9X7d5XkBkJ9CfURZ6AuiquOWHfwDyskktWu40cFyUTjDArgmSWnfMHJy4tJKP9P2tLaAAe+4iGhv0TNDg7vkLUCa2dkDe3vf9lEqXcyiof/E//7b5ri9DmclpFNnuM8LbU0urUKZZoNB4fVnfX6uDQvEsw/kBY8wRj6eOsUFhgha6ZjKOUNsG8G5Nzjp1qo6VIQZ4biRasL44wHqOSxx7M00t0K/X0fRifYQBLacP3q3St9zzfVCmNkKTko1Pf1Sle0fQcGViBk0g2m/TwYezm26EMiEzdXfuxWWXDvRbuwsDBk9dxPV09S+fUenhC5+CMqPuKcjb/tDfUen7b/xBKBMXcH15qauNPmILldvjEgXt3Tk93yZb26BMVSTOThvt/POCy3sGCCYwfT3F++1kaDARxnodzgcYGDs6gXBTs/9P7kLDnqndt0FefUqPn6TZgjKFWSOsQZOISOIYPhTGgKFwAogvX8B9ff2iNmmJI1xzi67TBsGsuRO4VxQNvL+eMXOInlmXY2RyDSwsFPkQN1vrz1E6kXg31nEN7Pd0Xxx76SyU+eoZXN+6i7pckqPZyOm9+/D7Em0u0j+Fhg+p4Jq700y/bB3n3zNP6v1+YQXnTJqvQF48rY0vdkzgmBp00ejr5aDX5r5j1NJznlfPzen1dHWI612a4VoyMu8bwzHOtdEYx+fMjH7m2HCMcDYDf7kihBBCCCGEkArgyxUhhBBCCCGEVABfrgghhBBCCCGkAvhyRQghhBBCCCEVcE0NLfIcRWepie6epk60d0cMa0mCcyuOYDY1YspmHT+XOiLMwkRS77RROD0xhYYWO3bu1+ndu6BMp6MF+p5/RyxRcDkaaeHrxiqaHdRPoYhvZV4LtWPuGEU4daiJVknWglOo8CKy67oHR8+aOjddGtMSRw9cGV989GnIm77lLpW+cScaKSydPg155zb0+JnZgWLy4RjH9GBBi0cXTr0EZS4uonh1+3NPqPR4gALe1t33QN7EIS3UTg/uhTJ7zx5T6VOPooB//bnPQ96u+9+j0mt1FKGec0S2U9t2q3TZR0Ftt49C45oxacgcoxrPNCUp9KAqHIF58MY5XmkTZb4FarhOdUdaSBwjmnGUGRoCbBjDlXaO692sczvvEi32P1DguF793J9hHY7oMdTa/TooM/GW74W85LAReOPtXTmZFuiHCRTspx00KZl+r65T9zMoAh++dAzylj+p5+iO73kAytyy727IO/aSFo9v9NGkoOEs37MTum/uu/suLFQR3n4ZRecVzl6cOAZFmZmj7Qw7vZ7g9+V9LTovHPOKumMmNb1Hr3nbb7wFysQOmlyUmR0vjimULeH0k+M3I+mkNjapdXDj29WaxO8zZi7rF07g923gfiU9vZ6GBI1VJpw2GOW6PUvnOcI1uYB+v3pGVSIiCxePQ15uDEmWnWenmRTr/szTeq8738Y18JGnHoe8HV39zLV/agrKPDfoQt7JZ76m0rmzVk+naHhyW0uPz10BTWDEmLS9+Z3vgRLtOs7bo89/VaVXnj8DZbozuF99qa+fS5bX0KRp2nnW7/V0uwy8SeOYVeTGcW3oGJvUG23IG4719WtOH28G/nJFCCGEEEIIIRXAlytCCCGEEEIIqQC+XBFCCCGEEEJIBVxTzZUbRM+83hUFnin1NDo2oG2thu+JEY+iQlDCmhNsNCnw3Oek0XTs2I7aqZldGHxvcrs5m93AM6z9oO/ZapRERErnzHphPpc6OrCde3ZDno2gt7CIuoHgHIOumwCrmRPY2AuKaM9Yu2/0zudslg3cWiXLi6jjGdd04L8jX8CAgR3nnHkwR9afevyTUGZiYg/kFWs6gN7y8nkoU4uOhub4UZUuUzwzv/3174S8xJzLlojLwZ4Hf0Kl187i+erFF45CXvfIV1R6/62o+dgY4DxZ+rnxAAAgAElEQVQLJlhlFEebNsBAg911fabdC4zbaHlBvvWYDoKBjYdD1G9IqvUGjdxZbCpk1Ee9yLDQ3zly1q0ixbrHns4rargG3n3fvZD3xu/UuqjyKK4bq089D3kTM7rvO2/+r6BMcjNqSCS19+OtHHa/8MpsQqzlyT6cvPSQ3gcm5EfxY/2PQN75Fz6s0q3DGHh7+52o8Wo8p/v4ELSJyHtveQfk/dUXtIbk+PnPQhmR/8HJuwJKHPvBbCDe0l13tIxNoxFsOfO4GOBaXYy0LiNxnmwmZ3EvzKa1lmi1h9f2ghbnRluc91EvI0O9ltRbeC/1tqOFSbUOZLiBQUyLMdZzcoeeQ2WJ9zt2gnzHoZ7HiXMvaQPr3jJ69YGjryoKHBul2dhtumq+eO5FyDv+9FMq3VvD4LwXClw7P/X5R1X62QXUBJ9aQ/3WbENPgFM2+LmIrDrNsGE0SCNHS7jLefad3an7frqGmrl8oL9w35veAGXufuA7IG/vwVtV+hN/9jCUOf0iavvSlt7D6mMci/NdzOsN9bgqI95vLcNnnskZvZYUzjo1zvFa49KsQW3UZW0G/nJFCCGEEEIIIRXAlytCCCGEEEIIqQC+XBFCCCGEEEJIBfDlihBCCCGEEEIq4JoaWniBYqMxavC0jVZ0LoIBQWNAwwdPRVszhhZ1p0420LCISHNCi0Xb0zuhTGsCBfOjXAv0emsYBLLV1uLmRoqmBetrKJycm9PCyWKMgr1px+Qir+v2TBxBezHA9ixN0LngmVd45iPGkcT7XHBcS6xpiWeIUhU3vf5GyOuOdD1nnaCprQbWqd7RY2PXHgzO22hNQ97cKR0wMI2OGcHxI5A3WtVjLNuD5hHTt2GA0hi0WLYsnD7fdoNK73vv+6FMb+nfQV53TgdAzibR7OXQbpxDRy+eU+nRCMd07oxzu3DkTiDlfhfnXmaClntBL2PpBDE3hhbNVh/LVEg+wOtbP5nx2DEDajhmDsYUZWmE/T5xE46Xzn49/i8++utYJkHx/cRb9XhMb8V1sixRdJ7kJtBmhvNvlL+g0hfmcD2/Yd8bIW9o1OOxi2OqcMZCfVqvp/WbsU6d99wKee0/+QuVLk9j4O3aPX8H8t7y4M+odNr/GpQ5+UePQd7nnzml0t0mGrX8LORcGd6csfuzt/d7RlUNY5yQOAY+A2duW9Ok5gwapPQaaB5x8rwOZJoKBjvftxf3q16q67l4DgNHiwl+OjmJ437P/gOQV6Z6XTx3Fo2UuhtoLJSlul1u2HUIykztuBny1i8YE5oRtkHp5DUntKnXYIh9XDqmV8EGnb7KhhYffOQRyFtf0X2TCo6pfIz778qcNr5YxKEvPedzJ40xRcsJXpum+Dg+Gut6OXHipe48d06v6fubKnFd3ntAj4W73o6mV2E3BtXe1dXz6P43YSP0Pv8JyBvN6b196AREXs5xL7KlUud5NQQn+LAJWpw7plOl8wpUb+q9vdtzzGo2AX+5IoQQQgghhJAK4MsVIYQQQgghhFQAX64IIYQQQgghpAL4ckUIIYQQQgghFXBNDS02I1xMHFFfmjl5xuQCRJIiEhzxX81Es84cH4zMiZ7dnNDi6s40CmY9U421dR1JPTrC3kbNmHrkKM7LNxwR/1ArgkcjbIPzQ4x4HYz414u+Ln1HoG+i0tcco5HMM6YIpt8dIbNnaGHz4lUUvt5yxx2QV2tp0WnNGStzZzAS+dK6MTvYiQL3coQiydXleZXetn0Zr/3YRyGvKHU7zdz5NijT2D4DeVLocbZ6Hk0FPv+MjmR/y11vhTL7H/x+yHv5z35fpfsnvgplJiZQQLvPzKtTC/NQRsQTSZu0s47UUxxjmZmPg14PyhSOyFaimXuOOLdSHBOPvun3Tr0OZcY5GhksFfpzeYbi6noHx0tc0+L/1SUcL7vvexPk1V5nzDEi3sv6HAr0OxMHVTqbQkOCQannyNk17Ku9+yBLTj6nTQL275iCMqUzXobzel2s13HtTPftgrydB7UxzKnnvgBl9r3r+zBvuzYD+eSHHoYyH378y5B3xpiB5AH7uCrcVRmMDDzDIscQyWwpxRDHSlJiH9dMP7S2YafPRWyDYaa/sOzifBmPHYOpdb2veuL8bdv0ntLfQEOdxdXzkDcq9Jj21p/mJN7fxsaiTnexTrsco4/uSkOlYxf7Kvf6YcI8gzkPXN6eba9+9WyqLrF6Edt4PNL9HHM0tGi1G5CXNFsqXa6hUYRnppSIbpv+GPcZz7jNGsFMBhyLkxHX/fWx2dun8No3vk4/l6wKrq8vHsP76y7puTaZoKnPoSl8zu2MdR2Oj3A+XlhA47b+SK+5pWMYkjmGFo3MmlXhPBqPsa96/SWVLpz9ajPwlytCCCGEEEIIqQC+XBFCCCGEEEJIBfDlihBCCCGEEEIq4JpqrkrnXS7LjAbKOcMenM/VzFnpPHfObzt3F4wuKolOENgangVtT+igr+MSz2avLKO+aWx0Ec0pPPM8Mt0w6OMZz+4Ib6Y5MavSIUcdz1IXz7A26/patcI5Yx3w/myM2czRwlk9l4gTRFjw7Gtwzt8H0edooyN9qYrzX30S8i5kWndSG6EObWUONUHz86YfnOCu/bVFyLtgzobvdQJ/jk0QQxER6WxXyZk7MWjq+jp+X7er63nhKOqiTn5Na0N2H74Pyhx48w9AXu/8SZU++9ijUGbj6Fcgb+8bH9R1nMI2ODvAM9ep0cd4AUqjownIjE6pVuDcD6kzXmt67Cfp1f07VcNZA8dG1zL21C8pnscfGv3EtgnUFhzai4Gvi7M6aHm+ge0ymjgMebW6CRbtVLOzA/V3aWb0BYWzJs3rdrn3htugjLfJ7T6k69TZge3kRURfXtB1mFvDNX92Zjvk1Q69QaX7X0C9WrmOGstyXffVucdegjLdIe4pEzNa9xWbjq62IrxAsZbUiiJFpO5oTOw+MHa0KZ6+ut7SbTC9Dcdv1sKg5bKk98dFR6OcRBxBjb4eB8GZQ/UdWhc1cCLAbiS4p+Sm3KSz703umIW8daOhTZzva02gZie0ddsVfQwYHJ046ol5IPDWwOjMIZC+XN0YwjLewDE0Gur+S526b0D4WpHBQF9rw7l24qzVwSjLEkd7Xzq6vcy03/YWBgw+tAMDUe/bs1ulp7bjGF6c1td69CsfgTIPv/Ay5N2750aV/qkbboIyE7MYhH7CRFweNbDtJqZxfM4N9boYEhyMZYGDKDe6s9zRLmYpzttWW7cLgwgTQgghhBBCyBbClytCCCGEEEIIqQC+XBFCCCGEEEJIBfDlihBCCCGEEEIq4NoGEfYMEGpawJbWUFgcnOBfVsBeODE8o/PqGI1JQnAK1Wso/rXBjbuO6HPVEST3cmPY4RhoTBtxY82pU15H4V3TtFXqiE5DjoLZrK7bvO4EHx4Fr/G0aNC5FZdNBQ30RNHm+zYjnL5SMkf4v35CBxpdnEfzirSGAsx2qkXo8+eO47WX0WikVtdmCuVLT0MZL5hj62YdaHRxEcXyTz32XyBv4cIJlS6mMTDld37/f6vSN+3bD2W8eb3nwferdPcCBltePIri/I0XdNDiQ3ffC2XW1lF0vmZNLoJntoLYpSWrt5xSaKBRGnOM1HPPqZB8iHM0N+vE8oYnjvcWBf257U7w4X0zGEQ4vKz7sOMEtGw0UXANf8NzOiJrYABLy2gZ7y8ua/OIZgPXSS9+7tQuvcZ7Aee9eg4n9Bq0PsA1aUcNDSaSvXqONh3TpPFzz0Hezjt00O5dXdwL69EJcruk96LaJAZJrg4nALxJO/GYpe6YCKTGtSh3jKPEMRpIjWFH1sTxVGtim2eZ3sc9I5zSyUzM3pR5pjeJXquzPq5baROv3cvNM5Hg4Kxjl0u0RlFOIPW07gRXb+g5WwacQ2XEYKvBGGikjnlFcNoumvXHGldVjRfcOJj1euitryPca9NElyu9h0wvYDZMAMeAocR2sE+i+532PDBwDMlO6fk/MYOmF1PbTKDxFXxumH/xw5D30pxe3/q3/yyU2Xn7OyDv6An9zDOaexzKvKGF7bJth563x1bQYKKPW7SUuW7P0jqyiUhaw7ExNkYYaeaYHW0C/nJFCCGEEEIIIRXAlytCCCGEEEIIqQC+XBFCCCGEEEJIBVxTzRUEhRSRLGuYNJ6BTBzNVWLOFydeEFrnDLCYz5XeefEE65Dn5sxximeQWy1szv66PqO7toZaLXsOuuHozqTE9+CW0QmF6LRB6uiUzKWiE+BxM20Xnai+nirK5vnaF7zW2AbV26zI6wpo78dAeDc1dSC+2V0YhDJNUZ83zvXZ+lYL+/PsiZOQlw302BiexTIxwfPw07frwL7HTqPGa8++myFv7rgOGrw+xvkZGzp4durMT69X0l26Pfe/9/1Qprf47zFvTuuwiultUObwHtSGPX9O6+PyTf7dCNYkR6MUHU2LnTLl1YxwLSJrTpBEG5i1KLDuuZOXZabHnOCK3loiudYguC3sBMe8UmzNF9qoZarfqjV5obG579+cRM6LnKrX/aTmaEqcbTWInree1lcGqC+ymhVHWiCrpafH0326eA41j5XhDBUr2fVibKfOWEmMvsgZvpJ5GigT1Fu8AMXOiI1Gx+sFuC+9z5n+8yTKYoIdN5zgx942G432xrt2cPZs+32u7tQZ+BBc3flC7+sCdLz3rOG1ub4/7zmiSgaOTrmwehyn6oWjgYpmrfT6r+49v5k27Tsar7HzDDTT1P21P8HnzoPFGcjbbgKZ33vvA1DmcyO93nzq0S9DmfmXFiGvMam1rx/56J9Cmb/9Tmy7O9+h9+3Fj+O+Wl/E5+OkqZ+7ziT4uW6Bfgdi+9jp5MEQAxmX5jkzXmGUa/5yRQghhBBCCCEVwJcrQgghhBBCCKkAvlwRQgghhBBCSAXw5YoQQgghhBBCKuCaGlpkjrixZvIyRzzmijeN0nVzodxQeF6mKI4bewLhsRb/ZQGFhW0nQF8yrQ0PagO8dsOIaIPz/aVjaJGUpg5jFEQnzrWiudYwR8Fn6Sk1TZ4Vd4qIREcIj7JXLOMZWtg8z2ikKp54/AnIG4y0MUW/i8Hr8pETmM607/rcOSgzt4RCyoMDbcowXsOgk9meuyBv2206b/roBpS5eA4D9q6NdT9MTmEA3ZEZUyhiFombMIVp3/J2KHPgQTTsePkjf6DSveMYSHlq8kHIu3FWi2XPLKMQN3cErTYItBdzNxM0EbH37AnFq6R0puNUS9er23UMLZw5U0adt+QEEb/Yw/E50dHBHPtOY3mBN6+0ZYqerldzA9fcqR0mGPAVfpdHFAxaXG/qQJjjDIMte0YYRaGvNcgd84ppvFZeWBMRZ38cY1/tmtZBdPP+1TQN8PbsTRg+eGYOiZ1XztrizNFo9w/PJMHbmyCwqNdOWIciWiMML5DyqwvhE6dhilL3ORhO+FWCxcsL6usaNxgjjOgtgq6phq5X4jzfpc76E+38cCN4V0ezjqZTeWLvGRumcJ6LcpOXZo5piNOnNdMOjRbuKf0h2tV0zDPlZAe/b3oW+2vvG2ZVunkTGkNdfFo/E5xfxn1gVXZgnYzB09IQn1Py5inIu+P1r1PpMv0uKPP4Rz4Peetzek7WSwwGXotoaDEyawCsESIydvr4Sg0sLPzlihBCCCGEEEIqgC9XhBBCCCGEEFIBfLkihBBCCCGEkArgyxUhhBBCCCGEVMA1NbTw1OKx0MJeLyJ7cATC1uzAi76ceEHMMxs6HsWUeYnCwlhqAaJnblAUKAist6ZVup3h9zVMVtbCCN+jAbbBsLduyjgGCI6IL461MHw8QnF14X3OCP0Kp7M8cwM0tHDKuBpCI26uVK6u+cv//MeQN7VtSqWLjQUo04sorty7W4tJu4vnocwoOkYqp19Q6Sg4Vqbv+g7Im9h3SKXvnUZjik//xe9A3uy+m1S6U0eR7aBvx7n39xjsvNyMsd4QhaOTb/xbkLfr3HGVPve5x6DMxgtfhLzZ+96l0usdNCNY7uG8tsYbIWI9QfMuOIYdv5lKCc5K3TBr2TDFdUMaHcgqzTp1fm0Fyjx7HA1Q7rz/Vn2dBo79ZAnHkFgfCqeanoa4XNdGDeU5NCnJpvbrDK8NHMy2I6lTba9OxdqaSk9O7YQyobgAeenio7pMivtHevAGyFvs6jZY6ONaXXPmbdHXa3Mc4HpTFdYkSkSkNJPGW7vzEvsKDB6cgR8dd5c41IOs8Pa0DOtZmHp683icOEL4pm7zZoLtmxpTGG/fSxJv4OEaBJTOglDqPvfMQOLY2dcH1hAFjWOs0YiIiH3aKRxjnMTZ2KGPr7IZULOO42xs7mfoGPF0Wt7aqdt45DwDjXKnHYyxWMMZU97+u3Nmj0pPTaExRbdAA6vB9AGVHu+6FcrsvGlSpffc9CKUWcjQDKSe6LVr7y13Qpk9t74D8tLZm/X3H94PZW68Be/l5f5TKt1cxr09czaVoXlvKKMzrr0HT/OeklyhkRp/uSKEEEIIIYSQCuDLFSGEEEIIIYRUAF+uCCGEEEIIIaQCrqnmyjt/OzZBSotN6mqCDeLnfKx09FuS6oKjEeowvEh7+Vifqa418Iz1yPnCnrl+vYF6mI4JKJc4gQz7G2uQ1zNtlzjRFSdqjqasr8+sjvp4hrV0zg1HE3x07Oiy8FMihQku6AVz89octFq+MKsSFrvYBu3tWjsVC/xbxGDstFOm+zir49ntWUfbExcu6owO6jl2vf6tkGfP1q/MYXDesxdQL5a29Pnt1hRqaNZOPa/S57dPQ5mdHfzcM5/5E5V+8ihqeO562/dD3j0P/KhK9y5iAOaVl16GvN6Lz6j0vsO3QZnFOdS+rUEMUScArJunx2I2vrqBMNMOnn1fN/M2OPrRRuZoJYzmoXCCV65fRP2mzOxWyXoN58PKl7+EH7tVa4nqh/dAGW8Bb+7SmsfG9ikoI5uREjl61fNf02Nh38278HNOcN7uV/TYu+lNeC/FGo7P5U8/otLtMAtlsm1Yh5fmdBDtJ5bmoMzLfUcnaLRZhaMNrQoveCxMK09T5y3nRruUZLhfiuB4HRs9ZW8Vg4pKYzvmGX2Fp+/2JBd9sxeN11HPUWvq8eMFMZch3l9inoGcOPWyuIRtYJ+vojOnums4pguj3fZ0p6GG648N0uoF3Y3uvq7zknD19nURkWYb27jcMMG5nWeLoaMTtlp0T5vu3U4R7D3jOLuzhnP09qiDgfdWnMF44BBk7X691mYnu3A/vC1ozdMPfTeOqduPPQV5d9ygx8JD994PZfbsfT3Ws6PX7/rMBBTZc8NhyNt78qsq/eYMP/eC84z11QWtfc0dLaEX6DuaabPZdxILf7kihBBCCCGEkArgyxUhhBBCCCGEVABfrgghhBBCCCGkAvhyRQghhBBCCCEVcE0NLYKrYNViMU+EmXrB8IyQ0DM7sIEMRTCIcOJcu8gxAOHaijaU2LkXBcmzu1HcXDNmFc0mCkMnWsYAYYxix3ZA5faqEaIXBQoSUwgCK9Iz4t/ECSyYOSreYaHbOPfa3AYIFJFoBc9Om3sBn61pgDUxqZK6F7ixtAJhnC7jERphjEdaONmZ2gFlOsc/D3l90++dO+6FMhM3HoK8YMSx5068AGV23PluyNtf18Fjn7uA93Lf3ffpOs4fhzJf/jIaaDz5mY+p9KIjpF5eWoK88qG/p9J3vutHoMxg+Vchr3fxmEq3JlG8fosJtiwi8vKyNvrwzFZyR6idm7Ula3rBQKujVcMgiXY9jU4gzNEA23hg57FjxvH0F9FAZ+FBbd6y93UoPj79OAZ9bo1ep9J1cYwFvMjCZp1wlpbNUccPdnboOdlbcgLF9rFddt30Tp3RwHqXL1+EvLk5PT723P1j+LkxrvEP/9Vvq/SpAQZ8zp16jnPdx03UgFeIJ/iO3zQpgnNIRCSaKL71+iSUGQUcm6OhDj46WEcjnNYMGobUTTDXdhPX+GYT+3hiUhv7LDvGOxfXdFDWfbP7oMzUXgykWizqPbvnGPGMFo5BXqOh6546RiPdlTOQF03beQYlsYbrWz83Qb4LNAzwsNt4eRX3dRGRhWWcM+OevudMnDnk/PZggwYHJ4iw83gjpTFSS50gwreLs/+GVZVu3HQjlLnnvT8EedP73qTSnhnXZEc/d77lrjdAmTfcdAiv3dD13NbCOSojnDMXLuq9aDLDNp/ehc9Ksy09b7eN0Kwmm8V5e0r0OtG/iEHogxMAPQZdryS7sgDs/OWKEEIIIYQQQiqAL1eEEEIIIYQQUgF8uSKEEEIIIYSQCuDLFSGEEEIIIYRUwDU1tCgc4WIwKmXPvKKMKBoUa3zhGlpgXs9E3S5rKKqrhxzyehtaZDpYRfHm9hmMsD3T0UriZhuFoY2aFsx5Qekn23jt7UMtLFxbnocy5xfmIG99wwpRsZ2smYSIyMgI5kcFtpONvi4iUkuNQNDpT29sYPTzK4uUvRm8OkGVnD9FpE6kdTFCzZm6I5Y9hyYQIdN9vP2+B6BMfQIHx3hVRyI/fQHHwaF3vQ/zWlrUe/zUR6FM2ZxR6VZ8Gcp89Yk/h7zlNT1fPDOS4cJpyPvcx/9ApdP3/iiUOfiOhyDv7Mc+pNKDExhZftu9aOqR79qt0ueXUPRaOiY7SVqa9FVeSoe43jTqRjScovA2H61DXmHmbVGgkProsd+EvKe/ptey9z74vVCmvYLi+5XPalOG9g403kh3vw3yRHDNuyKcPWXbQTOPcCkTiWg+JJmue3H+01Bk+bk/hLz24Y5Kb/+BO6DMM8+gEc1jXzirq+RsDo2IRkZjI9RuT1yZKHszeD5VtsW9fWE0wjHdGui9qd2Yws818F7GA72WdRfRVKQzhaYTuyb1+rZj+mYo02x2IK/e1iL+bdO4xgdj+DA5gfdSb01D3s0TWsC/7hhqFDmK+q0PReyhmdXaMrZBLPX4KVvOvMswLzd9lUScRKmzLhZRj46yuHr7uojIygoaoGRBj8fCM01zzA7K3N6jZ+rl7BemXNrCh4mp/Wj009mhx8eGY0yzHGcgL+/pMZs5jmHTI13PmyOOs9UFNKJaXNLPLic626BMf+0C5GVdPUdXRmi21HLM5GZb2uTimeeehzIbKe5ht2zXc7RR4jw+PYdmJxL1XG7VaGhBCCGEEEIIIVsGX64IIYQQQgghpAL4ckUIIYQQQgghFXBNNVelc4Y1s4EiHV1NmuFZUHuGuxzj+W3n6KuMxvrMfO7UaaqOZywTI61ZmcMzpaUTUHa4R5+fnpjBM9attj4LmjrRMosBXru/qs9dL1zA89SLK6uQV9ozz/nmNFd5qT83drRapROEtTR6Ea9fvCDQ9hh0LB19U0VkXjA5kxfc4MeoH2k19Vnf9twzUGZtHbUwtT13q/SOO++DMl7bLZ/XgX37GY6x/bt3Ql6j1ON8soZ9sHThJZU+8/jDUGati5qPttEXNJ1z/J0JPCs+Ma3PVydjbKfJ16F2avvL+hz2/DNPQ5nuC1+GvNn7H1Tp/gTey8L6BuRFsWMDilRK5mj7GnWtCRoNnDHsnLW3a24u+LnzQ1zffv/EV1T69tq7oMz2u1An2P/E76r0/F/8LpSZ/V4UEyQTt+qMNp7tv2IZpv2ctxOuolajXPqaSi989oNQpujhmrvnoR9U6Xw79ucnvvJZyFteNlqNFG94zVkXU6MTqDl6mKoI7oJuk85+4qz53bHRamY4Nusd1C2Pcq1FG/bweWDh1BHI23Gj1li1d94KZaKjy86Mlqjd2gNlEjPI0uDospw9pWbGYnsvXnvUw/myMq81rN4zSj5AHVZa119YtlDXN3CeEUo7pLCrJHGC5do7TrzxUyGl8ywzNuOxcOZQluCiYJ/NotN/qBUXSYyOJ81wLdsQDHJ9fmT6uY77+ClnrHdPa83hoIsavdlTWuM5fu4LUKY4j9rwhb6Zo4dvhzIb87hvd87p59NJ+1AtItEZCsH8BrSrg2O/m2Nfnbuo9VR5D/dxifi5LOi8ZIg6sM3AX64IIYQQQgghpAL4ckUIIYQQQgghFcCXK0IIIYQQQgipAL5cEUIIIYQQQkgFXFNDCwkoLLTC8OgolD3BbM1EzBs5gegKL1htob8vd8SHPXEErMbkolagiDBfwoC9GxtaVFerY2DKJNHX9kw9JMfvi+OhKYJlxs61CiPKHIyxDTyzir5pu6FreuEZQ+hy0elPR9ssJWQ6hSrCiwVs65044tXUqVPDXGx4AoPexYhjbPqud6h0azsGFfSMPwpj0nLolnuhzKQTiDIttPHG696IgVz7URuppLejycbNt+HnGnYOlWjIUg5RXB3WTYDrY2hCcepLH4O84QUTkNgZm3EVA4v2j2rji7133ANl1gdoclEag4CrK8kWGYywrXITcLEsnGDVBRqu2CDCEvFvbFmchbynPvU5lf692R1Q5u+9+x9D3uz9uu8vPotBdl/6vV+EvAOHvl+la3d+F9ZztxnXmbOleX4LJpj8+KzTTs9iIOpzZ39fpYc17Jcb3/HjkFfb+06VfvwvfwfKfPSjmLe2oc0b0hTX15GzJuzcps1iEpz+leEZBti12jMtcAMLGxOh3hj7ZbKOZgBJQ4/9UR8DqXfXnDXopWMqPeMYR7V2HoS8xqQx3slwX49mDUwc06RQYrvkuS63urwAZdbmMZj76pw2DAh9FPCnNef5qq33mW6J68FwhMFk02D3dWfNdZ4HUvO8k19FoyoR97ETnimj46SQF17ddduUbt29Z1i9LoUSTRk2VnDtisYcq1nDNXdlHs0q5i5qM56eM67PLmizinwDA8CXJV57YAzmuo7phTfWO9t129UDGsfVHPO6wjyfDof4uQs9zFswa0c/w31cnP1xbLo0B+eWzcFfrgghhBBCCCGkAvhyRQghhBBCCCEVwJcrQgghhBBCCKkAvlwRQgghhBBCSAVcU0ML36zCpo794XwAACAASURBVJ0yjvA1GLFh5ho3eDJzfa3SEVz2xyhgs5G4pxooHk8cceN4YKI7504YcyMI9modnHqWualniu/K1rxCRKRnPrdhFXwiMigwLzciRZsWESk8ZwpD2EQZETRvCJ4ytSJiiVOhzHUbYI+LJBlGs2+tamHx+CIaKaQdNKvYcff9+vtHa1CmGKBIecYIkuvjVSiz8Pm/gLzxsq5XvoAi8OGKFlOXayiuHnWxTt2eFkDnI0dMnqOYNFoTmk12eWlnTYq9laYoeo0D3VbNBD/XruHngpmziVxdUXbf0eLaNk2c+/PMBqxO21sDG4XjgHBBG+b8/m98BIpEmYa8f/Q9D6n04cP/DMqsPvYHkDf/pf+i0qMvPQFlJvaY75vsYJ2cdSqf1/0+WsSxKI4IvH37TSp9+Id/DK/tGNE8+chfqfTv/PKfQpmL53EMDc0alA+xTFrDtavbXVfpRrMBZarCa9/ECP+9fd0zA4jGSGnoiMlbCU6GWlsbShTRMQMarkDewKxTSy8fhzKNCyjqb05pY4GsMwllpK7b3Nv3xsMh5PWNqc/I9KWISDnAOmVRXyup495UNHB+Do2xQO6YdRWOoVYwfeyu1c7DTJro8Vpc5T/xp84zkAXNs0QKZ3wWdt13TK5cQwvzPNVIcVzvmHKeQYZ6nep1cf89fQT3bftMt+asZSsDPR+6jglM5szbTluPoZFj+HR+/gzkzW3ocdzvY/t6xmL2sc/br0pnDUobuu7tJt5LewLnyGhkDTSu7LmTv1wRQgghhBBCSAXw5YoQQgghhBBCKoAvV4QQQgghhBBSAdc2iLAXKNZqApwz1onzwcKca/XOzPqhDU3gO+8ctA2yKSLFUJ/DDNEJ+OZonhpW++GcYYUiUEIk2vPNIpKbwHe5EzS57+haeub2Rs47du4IjApz/t8LAukLxnQyddopOgH78Kj01QvVOva0KWZs1Jyz21MTM5CXnX1BX3vkBKHLMG/+k7+r0uc+6gTwW8e8sqcDmZZDPAPtnZmP9ky5F+TSBlt0/hyTOwG8gxnUaQ01H7UOnv8vW/oMdNJCDU3D+VxoT6n0uI2fC3WsQ5nqebzQQ32DpyOs2UmbXt0wwtEJ7FmmWhdVevPYW8vMPE6cTh2NcN2wU6SYx3P8f/Drvw55ayYQ9Qfe9W4oc/BdH4C8yX1H9fedwsCpa2d08OhGF4Odlk4g2lGp+2/q1gNQJtl/GPJad2ldZG8Sg3p++fFPQ96v/fYHVfpr57DtxjIFeVlD900xxHnsyT7qRjfcX0BtT1W4S75dN5xSrpLB7APevr5SLkLeZEe3nbdG5JmjIx7rcTAY4HwZr6FWa93klY5W025gXiBlb80Vs48nnmYo4PNHraPXzryB46k7Qo1JnpvA7dEbK87+6OzZluAE57UamqsopRYR1P+JeFpUrETqrOkYfNjRDTrr8NgEnT+zjDrsv+yhVnq6rrWEiy8fgTLrzhgamb3dpi/l6bWk08YxddshXAO3z+q1cthCfe5q01lzn5pT6f4GPqekjrI9mLzgCLOyOvZVZubkhPNM0KrhfFjd0OP/SoNc85crQgghhBBCCKkAvlwRQgghhBBCSAXw5YoQQgghhBBCKoAvV4QQQgghhBBSAdfU0MIL/gUqaUfzmTt5VmIWHUMCJwuFtc61vaDFNuBh3wksVjgCyMyojZPEEU5ClRxzDkcYWpj29IR3I0d0mtt3aif4KAQIvJSpk8ExQHAaNM20sLCRoWixEBQSg+jUE/9WhGdoUZrAf9GIS0VEtrcwLz+mRfaeiUnZQ2OKlWe1EN672+hcK1rhtBP0tjG5DevQntCfa+K9tLY3bAaU6SYoHpemrkPMHAOYoSfmNkFEbaBsEVlzAhLbcnkPxbJlD80OrOFDdIJnS8DxaoOKh00EqvyWcITTiWm+wqlnkmK7NzLdN6UTPzd3TCBsW5XO2tI/j/31of/4Kyq98vjHocwNe/4x5H3/j7xVpW868Hooc3Bai5SDE1DXIxoTlsEaBsK+mOOa8CcPP6nST3zmQ1Dm+MtHIW95VY/HvPCMlJyKmj71tP+e4UrXdEMSr14QYc8wAI2isI7unDHLm2c4NXQeCIoN3X+tBo7fprMutjqzKp33nMCxQzTQiKXuzzh29nV7z84e4xkEZbXEpHFdTuq45iZNPfY3xmh+Moo4zktrIuY6annmDsmrFXHJC20YEL3nwgqxz0mXePX12/MfKQo9rrwg7d6jkzUk6zrj+jnHiCra4L9uPzjfZ8Ze7uxr0Ty/RcekrZagCcSuvfeo9OoONPVZPnUB8gYjvQalEeeoN4TQE84zScH2bJnnmZkO3ks5xP2qntnn4yvb2/nLFSGEEEIIIYRUAF+uCCGEEEIIIaQC+HJFCCGEEEIIIRXAlytCCCGEEEIIqYBramghjrAwQrhuL5q28zmT9qJ8byrw9yYNLaxRQ+EIzHuOqBWNNvBz9vu8SO6+wYSpk2fK4F0rtZHjnUs7DROsYN65tnetmjEzyByBYHAE3tagIzqC/arIo2OAYIS+ZWxDmZoX2b2py6W7HTMJxzyibJnPNVCAGeuYN7RCbScSuTM0ZWjac5ijwLRnRNGpVZeKyEZ/CfKKoR3T2OfZGOd1asZUSDH6u6ubNiYNrkDZWUesODY69xcdU43SRImPV9Fs5XIlICsNel7VGpP4MccWJcl1n45yFL6PnXse2/HhjKmG1+4XdcHPXHwRygzTX4K8jz17m0q/bQbr9M/+x59U6YO3H4Iyzz6LBhNHnzyp0qe++ByUeXQRxf9Hjphrrc9DmZEzzkrjXODtTSHBsQfjzLm254PRF32tem1Tu+EVYcXzlzDzyhGcu8J0a5rkLPmeiYBd34rBEMqMxjh+mrluz0a9BWVqbTSPiDKl0rljzpOYvvL2VFDri0iS6R4djxxzGWetDgPdduOI1/Y+F62hhWPM5fWxXdMLx1DLM7mwa9LVXjszp42DGUPNBvb7KMd62ZUyhE0YccnmTDvc+WCv47RV4T07WQML53k1Nf3cTvCZZPfUHsi7YdedKr3vxpuhzNEdz0PeufRZXUfBOVqU+BwmxngjreEe03LMKlod3ad9x+AlcfoqmLbqOAZsm4G/XBFCCCGEEEJIBfDlihBCCCGEEEIqgC9XhBBCCCGEEFIB11Rz5b/JvfpZcOe4Nuh9vDPB/seMpsMp4wVFtBfzghZ79cSz5p7AydyL8/2e1sVqs4JzHjd3zvGmJrBo6gmlvN4yVSice/H6wdbd/T7nnsdWL+LWsxpCwPO/0ZwhHw1XocyxHt7vzfe+T6U7dQxeefbMMchb6+vz8ItnTkCZjW4X8kozjXfO7ocydUeUWBo9U2qD54lImerAf9u2z0CZYQ/rNDZtZ/VBIuJOmGL86kEabXBnETzT7p1x965VGMWKpw3bzLWu3si8fH0ngLUVNIwGGCRZHB3EeKTH+tjRouSO5soGavSC13rrYjABbAun/8pwEfKOf2VBpU/cegOUeWeh++uAYLDc82cXIO9XfuO3VfriHOqr+o6WIY1Wa+etZTjfoV2ctks87Ykplzh6A6fJoY2HfezPq4nddjw9iQfqjZ356KrMbBncL71A8WMTpHV9gGuZs/VKZuZjcPoc1ghnLhZD1ECVRneSOHtqM8WxYoODZxnOhTBy1oPCfp+jm/T6wcrloYRIcPZsqwfyAsBWibdfNMw4qxXOeudobWyg9ugEGne9BexY8J5l3OdHfS3Xf8DTM9q0s6/VTZ9OOMGqazk+F8009BzphmUok0X8XGq09k7sereedto6XSWr3T7kNSe1Bjk6Qe9l7OgZjcYxvcIg1/zlihBCCCGEEEIqgC9XhBBCCCGEEFIBfLkihBBCCCGEkArgyxUhhBBCCCGEVMA1NbTwgvOCUYRTxBPDWhGfK5f1BNebuHZmg7KKSGJFdY44Nc8doXa0AfOcelpjis0aWtjvCq8eJPXS9XVe6gSv9ESS1nTCE/pHL4io+T4vSHJ0A0rqdOlcuyoyCA8ooJwsxijSXJg/B3njkRZXTrYxEO6po09DXpnqIMLd5fNQxguEmdX15/ojrKc4ZhXgUOIFjzRtkDtLRjnGcb+xvKjLeOPe0wIXRkyaYdt5WuDCBMcsPBGqE5E0q+nrJxlevHCEsNGsOJ4HTpW0nODRvb4R35doaBG9AJMmaHCSYJ96pj4gNnbWu7EjHrdeKoVjAuGtN5lZz3qOMYUs60CRQdD0oljBAKHDNT2u1xxjAW+5aTV1Ww26jkmBM0Bt0Hlvec2dMWvjrbe8vcGZXANTLr+qjiubMDbapGdBaQPHO8FPN/uMsJkydr8qC2zfwjF3yaPdL5znAbOWZc76E91Av2Zt8UyiIo7XpjERSJx93TPsscGNPUMLrwPtnLXPOiLiRri2pgzZVdzXRZyAuoKmWsPCCaRe4ngZm73Aq3nmbQamaVJnzfXHsDHV8oJAO8GOUxuM2zOKMOOj55hzLHbRrKLbP6uv08N6Nx27ipppl4EXmNpbS0yx0tmPQ4btGaPO6ztrvOMLI8XYGq5cmRkQf7kihBBCCCGEkArgyxUhhBBCCCGEVABfrgghhBBCCCGkAvhyRQghhBBCCCEVcE0NLXzVd/wmqct5jnmELWcjYIuIHynbGmE4RhG5I2C1MrvSUdUWTh7UwNEspqZdEqdOXrtYYagVpor45hFWNOgJUb1I4DbPi3xeq6MBgTXM8MTrXj2hjOdkUBENxwxESmPm4IhJxRE7Bvu5EvszzdA0pTQGEzWrZheR0RjboDTfN3aijmfBMS0wotPg6TZNFaLz95h6vQF51oDFi47ujfPM5NUaGDVenPE6NmPMW9i8+VGaPE/4G5yxAeuI075VUjprUr2uvzNx6jka4OcKs1amjomHNewQEQnGiMKbx0Xx6uJfr9+DtyaYOux2DDR2mVtOrEmLiCSOkLlm2rNw1jJw1BGRYI1hnDXJNQMy4ypz5ra7f5j1JXHGWcu6LYlILub+NmkocSVEz8jAfJ+7vHuGU2Ai4Bkdec8R4ZukvlmuybPuKyLu5mvvOTjrou2WxOnzJMH9cmyMMLxnjbHzvFOYPo8lGhsF5/6gxb32dU1ojPmIM/e8FrePgV6TV4kzOtHIZBNGY5c+aEw8PLMM75nL3HRwnD6CY3hiW7DmmK2VTuU306a5KbQxRlOPhXU0tOgNLqp0Z9yGMm3nWT9LdN29ZdJbO60hWj3dnAHT2vq6vrbz/JaUzrOSmUdTHTST2gz85YoQQgghhBBCKoAvV4QQQgghhBBSAXy5IoQQQgghhJAKuKaaK3vW/xLm/L9zht0GFvRwj3Rvok7eeXEvQLA9CuoFfPPP9pqz4M7ZZStHiU6gWC/Aa/oNTpa/Euc4PhzAj5mj8fICYYLuwznr75zbtVXPPL2RG11Z57m6iIrIvL8zQKBqTxfiBW7W5ZqtCSizY9cuyJtb1kFhvQC6IniO3moSgzN+sxqeG87M9YNzL4VpF0c6JY3ONsibHumzzF0b8Fb8M/pwdNo9g43LVtOMKS94bvTuz6xJNhjxpSo4/W7OfXtn4auk28d+L83krjt1iM6wtjEnh4MBlHGDOZrO9+I0u4uuWQO9v+h5ehTQ1XqBMDeh1fQ0evb+XDWwF5zX6LdK56x/zVnjbTTgzNENDJyxZ+NzD52AodERWFhNTkiv7vi0WH2su1+6gb5fXQPp6QHtPuv1nS+nstpJp0pOMF5bMJbOCLJ19+7F+0Lbds4khiDNIlKYcV56EXydRrDD1btft+3M99U8rZYbUNsGmPYWkurwlEy2Dl4/RDf4sL5Hrx9cLaEp5+nc3Ydx97nI1MlZO62ILLgaKKNTdobiaLgGef3eOZVujqbx2s5YyMwa5GnovedjuxN4OjcvAPtgpPe1Zh1HQqOJ62KnqZ+VWi0MQr8Z+MsVIYQQQgghhFQAX64IIYQQQgghpAL4ckUIIYQQQgghFcCXK0IIIYQQQgipgOAGPCSEEEIIIYQQ8teCv1wRQgghhBBCSAXw5YoQQgghhBBCKoAvV4QQQgghhBBSAXy5IoQQQgghhJAK4MsVIYQQQgghhFQAX64IIYQQQgghpAL4ckUIIYQQQgghFcCXK0IIIYQQQgipAL5cEUIIIYQQQkgF8OWKEEIIIYQQQiqAL1eEEEIIIYQQUgF8uSKEEEIIIYSQCuDLFSGEEEIIIYRUAF+uCCGEEEIIIaQC+HL1GiSEcGsIYRBC+OBW14Vcv4QQPhhCOB9CWAshHA0hfOAV//aBEMKxEMJGCOHhEMK+rawrub4JITxyec3cuPzfC1tdJ3L98iprZzuE8B9CCAshhNUQwqe3sq7k+iWE8NMhhCdDCMMQwm9udX2+nQgxxq2uAzGEED4uIi0RORlj/Mmtrg+5Pgkh3C0ix2KMwxDCHSLyiIj8LRGZFJE/FJH3iMiLIvJLInJXjPHdW1VXcn0TQnhERD4YY/xPW10XQr7R2hlj/NLlP5pmIvLfi8iSiNwXY/zS1tWWXK+EEH5YREoReUhEWjHGn9raGn37kG11BYgmhPB+EVkRkcdF5JYtrg65jokxfu2Vycv/HRaRt4jIH33930MIPy8iZ0MIh2OML137mhJCyGuHb7R2hhC6IvIDInIgxrh2+d/5YkW2hBjjh0REQghvEpEDW1ydbyt4LPA1RAhhSkT+pYj87FbXhRARkcvHV3oickREzovIn3/9n15Z7PL/vu5a1o0Qw7+6fNTqsRDCg1tdGXJ98w3WzreIyEkR+T8uj9VnQgg/spX1JIRUD1+uXlv8vIj8WozxzFZXhBARkRjjP5VLxwAfEJEPichQRB4WkR8LIbw+hNASkf9VLv1ltr1lFSXXO/+ziNwsIvtF5FdF5M9CCIe3tkrkeuYbrJ0H5NIfoVZFZJ+I/LSI/FYI4c6tqichpHr4cvUaIYRwn4h8t4j8m62uCyGvJMZYxBg/K5ceDP5JjPETIvK/icifiMiJy/+tiwj/KEC2hBjj52OM6zHGYYzxt0TkMRH5vq2uF7m+sWuniPRFZCwivxBjHMUYHxWRT4nI+7awmoSQiqHm6rXDgyJySEROhRBERCZEJA0h3BVjfOMW1ouQr5PJJc2VxBh/WUR+WUQkhHCbiPyciDy7dVUjRBFFH10lZCv5+tr5Yeff6CpGyLcZ/OXqtcOvyqXF977L//2KiHxULrm4EHJNCSHMhhDeH0KYCCGkIYSHROTHReSTIYRmCOF14RI3yqWx+0sxxuWtrTW5HgkhzIQQHro8LrMQwk+IyLvk0vFVQq4p32ztFJFPi8gpEflfLo/Vd8gl19WPbWGVyXXK5THYFJFULv0xvxlC4I8uFcCXq9cIMcZejPHC1/8TkQ0RGcQY57e6buS6JMqlYyxnRGRZRH5RRH4mxvhhEWmKyO/JpTH6BRF5QkT+xRbVk5CaiPyCiMyLyIJcsrj+oRjj0S2tFble+YZrZ4xxLCI/KJeOrK6KyH8Ukb8fYzyyVZUl1zU/J5eOqv5zEfnJy///57a0Rt8mMM4VIYQQQgghhFQAf7kihBBCCCGEkArgyxUhhBBCCCGEVABfrgghhBBCCCGkAvhyRQghhBBCCCEVwJcrQgghhBBCCKmAa+pnPz29A6wJLwfM/f/x3AtDgu+ASZKqdFkWUCaWJV7LhJX0ru1i61Xg95XifZ/+Qi+qpf1UDM79Sgp5RZGbKuL3Jwl+o23jLPWGAX6uNO1ZOO3r9t+rX1qwFRDv2t3uRiWBQtvtzqvaZm7WWBN6zw66b5AHPex8n9dKpen3uMnYqXZseiRQxqmU0zAl5OF3ud8O68Grj4tvcjV9LS/P1DNxSvnd/urf1x90Kwtie9etNzkTS1++LDY3HzfjEBucu3ZWEsix67KISEjNWu19v7tumG/01mqTlTvXKZx2ycSugXjt1MkTs57mBX7f2Pk+uGevns5Qt2tsjLjveIMsdfYQy4kTZ6oan68By+F1lVo4/Tko8fE//TjkPXvknEqfmh9AmcVyB+SN9hxW6QfufzOUeeOBPSrdbjegTCPmkJcOurpOL7wIZR4+OQd5N739bSr9D++/A8oc2D8BeSG91rG2zUAvhlgkbVVWqfvvOgzjM5b68jffdgg+N70T+31yckqlp6Z2QZms3oK8vlkDw3QTyhzYPwl5q+e+otJLx05CmTc/8EOQd9/936nSn/jj/xfKLB/5rEq/9fCdUGYY8dnwkS8/rtIvLi9Bma7zTPn/tfdmT5Zc53bfzswz1jx0d/WIRqNBgAAIghRB0qR4yUtZN3SvFVKEpPCDQn7xg/8F/z+KsMMOvdghh3wt81rUHUiRvLwYSBCNnoBGj1Vdc9WZTw5+AP3wfWuBZ7uUVSAV6/e2d3yZuXNPebIq1/qW1tZMuZNPICYhdX/8nR+a8r/87ncg5t13/hzq/sN9m8Uo6dyEmMNDXEfP9nZMudFYgph//T//rzPnp/5zJYQQQgghhBA1oJcrIYQQQgghhKgBvVwJIYQQQgghRA2cqeaqLPH74iTi2/AyJ7oB0BIRRQDRBKGmA79h5xoSe66EaRnwTFBLNVfuXFXCzk0VI7ZE9CkF6Tvfipx89x2juWL9xNoZ80E+vz/Xooi5UiuVH7s47VTTf19NTz17jnF9FemnCF1fjEYoBjoGTOvnLherV4tZL3RGw/ViNEORurOZEacvOimZTAn2t0itnT8P0WXyAbPXQz0ejnsIIRROn8rmNTuXP1nFRXo2JnKigRaWXL9B5rrfm0umnSR1EcpFOnygn4zcA38PRFBnjO2XMmlBRNlEnUvuxjMv+xBTDMlvhMf2mflLovmehG+b8jevXoGYToUar0/u3jLlH9+5BzHPWqgDefuK1QgtXkYNT4KSyBqZ/RvlM2b/jqiTtIlzYTSy2p69wwHEvPrVt6HuT//sn5jy/hHqxaYl/qxeu3jJlB9v/gZiLhVbUDd049x7CXVR330dtXXPbv/SlB8+eB9ium45/OSj2xDzYKsHdb2x1TeuL69BzGoD++Dw6MiUt/t47pXFFahLE3v+vESd26DAub7x8lVTfuGNH0LMv/vz/wnq+s/t/bXKk/120n+uhBBCCCGEEKIG9HIlhBBCCCGEEDWglyshhBBCCCGEqIGz1VyR3FAh2Dqei4Z825/a42J1LZDnisoNYvL2sAtiVVSaIK+dorolplSYfRz/ntnlx2GCjhiicxD9zsv/tm72d60nbmcMtOtmTxb21wnQzM0egt9W+bPRyUKOmz3JaL4jV6Y50XwUWYtRXyRHf7bsrkcXKFZhHiHSBDrHvPaGXI7mZfLnJqeukZh8VTw3FRkvN82olonMhbTyB8bl1QNdFMuPx3JmRWzWoDpjGqiIXIYsL1TG1oM7f87yTpGx8mcvI9WEvuns/qLShp32BP3CaZrSwTHe72CKP3eKxB6XZE2IqfIjqJv2rS7jkOhH8qnVZbXe+CrEJKNDqHvy2Gqsnvcw5mH+DOr61b4pp2f66y6EKH0VqztlgeDC/CrUTXObmylNUcP2J//wH0PdN75p85ntHRxATEl+FSyv2ja8dvMixIRHm9jONdvO+WvnIKbZQU3ZT/7d/2nKrXQKMd05q2/aOdyGmDzDvFPzc1bb993Xvg4xS6uogXr31k9M+YNP9yEmDcSXobS56B4dvQsxrYuYW+zvv2nzYTUWLuP1UtTMLSzY/lzq4vyJQf+5EkIIIYQQQoga0MuVEEIIIYQQQtSAXq6EEEIIIYQQogb0ciWEEEIIIYQQNXCmkseYBI/c0AJri2K2mDtKKVmn0DfG8yLKF+NkSYRPTpxxgoeLq2e3kybjZUedcnJBdzGsizE/IafyvhtUuh5lzsEMCpjo3WWGZIYsMWYnEQmKORHJlSPmReSZP+coP1hxawjnIjGAiBj3056rrA2+ipky8Pli4woSQw18nIGFP08IISSszl+f/E2Pmw/Nnnv+/hoxiXhDCGnEeLHrl06MT+cUaYNf7sychyWB9wmJ0wz7jm0lkPC9piTiv7+4cSHrvyQGJVnDGlg0W3MQ027j1YpyaMqN0VOI2f/YivP/Yh8NA6YZZvVNKptMdryF537eWIa63tiaD9BHzKlOg7gHZFU604ICzRYS9BU5MVc2rkHdeGSTRa8soWnB1St4XLdlzQ6uXLgQ1QbfDQuLaPiQ38C5lyTXTdkbuYUQws7j+1D3bNvOoUaCP/WbiTW0WJjD/WdtiPvNxqK95//6a9+CmPPfeAvqXv6ZbUP6V5hAe/8ADTSuXbTZjlffwHE5t/A9qFtbuWnKB8/RdObta2gyM7luEzVnZI3GoP9cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGjhTQwsqkvYiyGhhM8v8PRs4+wl16FQXygwe/AWY5jPGAOEUlajszFzE7yvjxipGmM79JM5OhF1FtJuL7vFcYLbC+hIE54RIsxUvXo81hYkzDIhoAxGKz7aJ+JwV7IX/MXtGwHuJNcKIaidpQ1XNvl6d0PGLOC6NWY9kLjLDBW+uEG+8czJnGLhnclzqzp3QscJzgxkHaVJO16g30CB7foOYFLhTlRUK0xPS5378Mm9eE/he4ptF/B3+C8OO58I8GgYszqFhQKdpnRM6xL2ijYeFpGGNDTqdeYg5GFmjhsPqCGKOhzgwnTAw5Wkfhfjd9RWoa07toNPpezJt/n8G7Nlgx4rtNXXup8uXLkNdunnPlHvjPsRsHh9D3QtuM2lFPqN91NFwCDF3H21B3dNHd015dYJtGh+hUcrw4NCUFwsyDgM7P4tjMg69HOouvbBuyp3XX4OYuYsXoe7Fr7xpyl97cg9iPiF9UA3tvTSfPIGY81exDVVi294+xj74wR/9M6jrrti1/fDRBxATg/5zJYQQQgghhBA1oJcrIYQQQgghhKgBvVwJIYQQwzQWMQAAIABJREFUQgghRA2cqeaKgZ+sRn7DGqPjYcfFnX12RGTeXdTtsJjZV+fSk9l6A67b8Ul9yWEn7rz4tK/mqIiExDFjflKYNsVfPyLP8G8rZx9XZ/JqaCcPwipfwfQ5s0N40tQYTRnpPdQW0dlJ6k6WkDju1DF7zemqrgrSnz6hbEK0b3Tc3bmY5oGth8zplIj8h2oXi8Lqi7xeLYQQAkmA7Ls0Iwl0s8w+wrhmjtS5+eKTA4fwOYmhXd95HdpnjWDJlW058yKsEJeAmc5yOvVOlrj9Dxd7v+loABGNHtZVra4ptxYwe+2FJo7LtLDzblCiVqssx6Y8GWPS1LSDi6gRbELb7iuYNLW9soR1fdum3R1MyLp4vgV15PYi8bOR7PkkMXYxtXXFGJMIk1zOJ6asDqAuzWwbDns7EPPuh+9B3VtvvmrKrSb2J6PXt3vgh7feh5gf/e1fQt3hU6u3eyXFeTY83IW6/pbVkKVj1HiNJvaedweoO6umY6j75NavTPk//pt/DTHf+8H3oe7gnk12nPQxcfNCA9fos4e27Z29DyFme30P6iZuYk9I4uab3/5voO7cpQ1T/vCjX0NMDPrPlRBCCCGEEELUgF6uhBBCCCGEEKIG9HIlhBBCCCGEEDWglyshhBBCCCGEqIEzNrQ4qQlFhBiX6YpnHxV/sgidfVTCTnpqJz6ONpOIMHyIMTJgnLjzTpatkorHTxBzUrhZhq1LI0XvUR4tzEAjKq/w7L+HsIgqwjCACuoTK7hOqGiZJSi256LJZZnTQFSianJYxN+J+PxxCZgjHQPSNMK0pE5iknqTjYMbNbgKmgSabajONIDMF9pO3wQS0yZmFa2GfTw1m2g20GxZgXezgQLzgozNJLeNygsU1ecFJtCcjK3AuywxpiRmFX5+pqTP0wr7ACwDIpMkV+5cPBn3f0lY84b5BRyDZqcDdUtL1ixiv8RxeT7Gvjs+svPlYIAxBxM7V0YFJhouyWLIEpeguIXzfr7Eup/+jTUaON7ah5jvvI3JVt96xQr4z7fQZINUhbK0fT4h5gfFlKyPqe27aoRGH63V83jBE9IaYuLdTmr3lhExfHj68X2oC7lL/o3DwJ6Q4eEzm0D69oOHEDM+QFONjbkFW7GD5hxbdzAZb2/XJhbuDzGBde7GZkL2O/aCcNi3/fnuLib+3fkNmkA022u2TeQHz+6IJBFu2j3+V8kmxBQpmo80OnasNq6/ADErr78Ndeeu3TDlRzt4vRj0nyshhBBCCCGEqAG9XAkhhBBCCCFEDejlSgghhBBCCCFqQC9XQgghhBBCCFEDZ2pokXyOXcUsoqS4kYJdiIoxJCC1zLwi5k2VierL0gr7qKEFP9vvKP22TUx07u6FHUcNCPz1ahVJs14/OxF2Sq7ltc2xt+vF41GGLIGZapALEmOKLLMC6KyBKtskQ6F/6uLSBFXLqZ/VVQExgYj6p66uLFC0XBIBdOXOXxGBOZ2Z0OdxgwXGG2yQmYPGbJ+aWqFmOe4e6f4TUUl9RagRzmzzj4zsN3MNO6/aWRtilttoNtDNIkwgUnvuBlkfJemEPLONz0m7p2QdHTmTjQMixq9KXCOJNwMh85rNMzCiYM8rOmX9GEe45fxBY+dUP1+FiHzhS1C3df+5Kb/3SR9iPu7jeE6Gdn9bIUYq3dS2aZjjfpeX+BNsWjmzhREO8P7xAOqe7Bya8nv30Bzgp3efQt2ffe9NU/5Hb6Dw//Iy3l+oeqbY72PfDYcTqANDiymuoeUrL+L1TsjNjWtQt7Nrx+Jo8zHEbD16AnX52M2FLl6PPQu6zkylkSxBzPwQn7+TLWsMcefWbYg53MZ+LwvbzgZ5Hjabdp7NddBwJWPGW+4OxyNcH3c+QpMNv1cHYtRSNsj+3bbt7HVxzVRz2M6u279X+/g7pTpCs5NiYusO9z+BmBj0nyshhBBCCCGEqAG9XAkhhBBCCCFEDejlSgghhBBCCCFq4Gw1V/Sb8pOdC7URp6v/8dol9lbqtVMhYDu5lskdw7POssBZFaEgbcJxiEh+HCLbHjEMXHk3W+N1mlQRCZgTlmyV5dQFTRvTyxBcGxKiTWk0iTal677fTnFZ5wG/5y5LO4unLNsqJFImESSRYpK6b75L1BuEKeoGCvf9fU50WYHMadQDkhB2lJe0RK0znK9fRI5Wv0ZZ29OI7Op07dEk6Xb02ff4OGNDWGhbvcZCaxmPq0iCYKfTKwr8tr9yWqKCpPAsSXJen+qTJQhvptgvi04TkM4vQszxGL/tHxU2SWlSYdLiij0MXZUfgxBCSEg7E5iQp60KPEPIYssP7D7x0a8OIeZH7+xC3S9u27idHu6dQzLPm+vnTPmHr78EMZdGNuHr33yKup6PdzB57XDi9XJk/rKpMrZxg22cYx8OsQ3Dnl1ne8+eQ8zbN9egbmPenr8YoH5lPMD9ezS195yTqfnGN/4rrDwhf/qn/xzqesWPTPnR5jOIOdjG+xn0bcevruD12Eq7sGafv+kI5+Lg7gdQt3v7Q1POjzAZcEb0fgtLVnM4v4wNXVqzCYpbbbJ7k7mf5y75MNGdTnqoAxsfW43eZIRzvyT6rSS37eo0yPODPFPKxK7l5QbqMNM+jvGH7//MlHt7qF2MQf+5EkIIIYQQQoga0MuVEEIIIYQQQtSAXq6EEEIIIYQQogb0ciWEEEIIIYQQNXCmhhYsQadPsMqTeMacPLoV9tQsGTAzLnDlGPOK317Anpu8z3ohuk8A+VmbyHGVT+pJEryS5JH+uFixs28DtRWg13P9Qu6PAmYDp+caUFXM1MMn0CXzl4jJ/ZjHttqbVWQtFBGnTUz0V7jrTXMcg4Iab1gSMjd9YmFmGMCqfPJfNu8bRIibJjbpZDNDAW85QbFs7u45JtFwCCS5KzNyYeJxyO16yo4WEQYzbA7TVsF6JJcjR/q9ukX2yZUmiqJXutb0ISvwuGKCoui0YdvQnMO535qzouw0Iwm0SXLssRNhD/s9iCkmaLiSjO38nOuQ63XRdGY8dMYbOdmryULyQ8rmGZuzeJ4/UEMLMoGHR7j+P3jvvin/H3/9McT89MMDqNsf2fmK8vYQzm2gEP6P3rhuyt97/TLErFbW9GIBvU/Cf7yFSX1/tWmNIqY5zl+6aN1vkrIiSWl7aLby4GPbLz8aoxHG3s4c1L26budwZ4p7dTVBQ4upM3fJWyRBcY1c+XtvQ93ld+386JJ942gf96QHn9h94soVMqhk0pZH1jhl+52/gZjtj34FdZND21cNsgeuXr4EdWuXrpjy3Ll1iGm7ZLytBknOy+7FGQuVY0wUPSTJefv7dn709/YhpneAdeORPX8acP1XZI9PVq3R1zFxTrl/hOtva8vu+9eu3ICYGPSfKyGEEEIIIYSoAb1cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQNnamhRRoi+qeyWHBejH2ch3sCCifgTcmBZWhFfrHzdm0CkGXa5bwMTH1PRsje0YGYZxHjDCxJZDBNO+zhmvBFrjoHXiznT2Yqy0TCAWXgQXL+wbkqzLtQ12zaLekJiJsS0oPDa+CrWMMSdixgU+C5npgmMZubmPZm/JdH0l4kVmGeNJYhppER4O7Ji2WqKomxmCgHGDWQe0rb7fjjlqdlibXAbFduTipItLGfiwVYa229cVbuBIuLlzgLUNQpr8FBMUOy8sIiC8qVVawgwd/4ixHSXbUyDGGqwvWXiRPvHu4cQ09/bhLrewZaNGaARRncOxf/LHStEP0JfgTAp0EAjBLdIIo1T/OhlxBDpDwLixLP9YAvq/u1Pfm3KP/5wB2J2hjhffXeeX8P5++23XoK6P7p53h63gntSM7Hz/u2v4HnGZH0OC9v2j7fRFGJckGe9H2OywabkGTYZ2DY8eIJzupXh9cqJjVudPoeYZITn6rTsPG+3liGmTrIG7i0LS/ZZ2yYxh2Ps96dPnrgaNJMIARf3kw//2pQfv/d3eNQRXq/bsXP2/LUrELN6/UtQ1zlvjTbKBvndkNlz5ykxhWDPBv87kJkIseOcwUorwePaJc6zYmrXQz7CfTIjaztdsHXLKxAS5pdxfn7l2oYpj3c2ICaGP9AdVwghhBBCCCF+v9DLlRBCCCGEEELUgF6uhBBCCCGEEKIGzlRzdVJOmqCT6gYiYmIS4TK9UZKR7z7dt8q8TbMTG1Ni9GPZbD1FSRJaViV+N4zjwJKysvd135+zE++ysOh+OQEFuV+4HpkXBUu8676jz1JMktho47f9VcPqMnKq/WMZbWf/jeSkXed1ZyU5T6OJ835x3uoN5tr4ffVkhN+YHxzb76nzAu+3QW43a1oNTUX6ifXdSRNTQzeccpLWBaJvmrhLDqa4jkn3wR03SR+wXsnct/XdFtENkuOmI5v0cXER5/7apQtQt3zBaqwa6+chJnVJhJsZrrWSfMfvE18utFEn1exgn2ct+8gcP3uEbRrivF7r2nYVZD2MSZLL0m0CTB9L91yfyPy0k1yfEr0D1Fd88C72+U8+3DXlzQF7rhO9s9MffuMqami+fxnnZukSXB+ThdZ0GrpHe6hJunTxGtR998jOjYOjTyFmi8jz8ijhJ3le+Yoh7iP3n2CC4LRpr/f3zuP6xHTaIVxcs8+5pVGklvmEVORBmjkNUqOF67EYDqFua/OBPXfABMXjx4+h7uf/+/9mysNnqOfMUtSLrm/YuXfxEs6X6TwmFn5y4HStJSb6nZ+3+/fiAuqbF4gWbeqeM58+wUS8u73ZiX67ZLrOr2LC7rncPtv7u9t4brLnLrjZ15piwueVgDrejcq24c4xzv0Y9J8rIYQQQgghhKgBvVwJIYQQQgghRA3o5UoIIYQQQgghakAvV0IIIYQQQghRA2dqaMESi534XFEC8ljDhVlH4XEJS8pI2lT4hGtg7oDJlVOSJDVlBhqJPRcV7Ed4R6TEiKMkvVAW1vSB9xOrjGlTjKj+9ETZ9MwRhhosAWtwiaKzNiZJbDRR1D91HUPNCKLMK1gCWGZsMrs/fYRPih1CCJ0Oil4XF6xYluQwDOMRimx9IuyKbFE5aXejYQ0JGiT56HgywkbAHUYmLAczmdOlIGYquavipgUsmaMtl+TcDZJQesHtS4skeWSYogg8c8L3zrkXIWYyj8LiPWfwMj5GFX/TLZLFpTU89wgF+kc7NjFlOcYkwqw/k64VOy+sYrLq6SYK2lPXL022IEii1jCdbXbE9y53HIv5A+DuQxTL//guCtof79u+K5jzDukFn4h7oYsmLfu7B1D3H975yJR/8K23IObFebu/3foYjSnyAvfA5rwV3hf4eP68TcmWWFJ46h3hjqvwggUxuTjYsceNzuFzrrd/H+qe3fvExhxgwud/xZp5QjaP0Vxhf2jHtCLrsSJJvR89f2DKzMjk7n0c51/feWjK+QQHoj2PhhLLGzfscQuYCff9e7ehbt8Z9ix10Ohnednur1Py26KcQ7OMTx9ZQ5lf3f0YYua6xBxjzrZhTHaurIMWKPPr66Y8GeC4TIa4jhZS+yz4ysVvQ0zjEE0uPnpozUYmXZz7Meg/V0IIIYQQQghRA3q5EkIIIYQQQoga0MuVEEIIIYQQQtSAXq6EEEIIIYQQogbO1NCC44WEsaYFs49j4l+oI2JuKmROZ4tFK6IW9aeigmTXhqJEAV1KRK2liytLdn3y/uzaVGXEqIFe0LeLqGNZn0ObmGnAFyu5TsjfGfwYp9QAgvSvE/o3WijSLMi4FKU3c2DzlzQB4iJF7xFU7oLNFm4Z3rwihBBazsRgNMAM6oMx1hVubrB2V0RwnThDi7REo4EkR7OFypvA0LlJGuHPPTvkP4vjKe4JfvWxNRTj+1OSoCa5o/WGFSQvpW2IKXI0DWms2LjG+jmI2a5wDm1tH9l2FjhfFhacycYUYyY9nAvFgTWwKKscYsak79bcXrmyegFi2tvHUJcU9nppk+w3TRSdpxPb9ozsuVOy7xfO0KXBzDJ+H3Fr7dkOmh385tEzqAM9O3uesPXh9uF7T55AzKePcf7cn9ox/toAN4ncGf2MDnH/ufsMDR/GzuzoeIxzkz0/Kvd8Suh+wNwxZm8SaYHXG/fsuR4924eY7S00d+jtWTOJ9SbeX53ce3IP6h5tvW/Kwwmu2bLEvezJczs/Pn6M5gp3HuG5Nvft2C8mxATKGTeEEML8hjWwuPUUzSMOemjwsrSyYcqtFK+3d2DbnjfQuGU8wbnvTWaSLppzXbn2AtQlztRnd/c5xAxbuAcuLdpne3cBrzfu70LdpGefmetzGxBTltife70PbUyCx8XwB7LjCiGEEEIIIcTvN3q5EkIIIYQQQoga0MuVEEIIIYQQQtTAGWuuTqb84AmDZyf/ZAmDExfn9U4hfE5i2IgkwixJcuaTjVKNl6tjl8cqTBpMupd9a18WPvkwtilpEF2Lv+cCdSA0QXBEzRdNxhIu+rGj0xD7N204LQr53jkv2d813BxjlyODnELDIvvXn4poytKWbfvSEmpjFogOq3BJDHs91BuMiI6ogETYTCeBdROnCcga2Ca6FiI0XkyTVLk1c3rprT+D5ETGCRm1TyJsv2uQxOKdlhv7giQRJvkW22s2oeR0FRP95k9Q37DodDQ9suceDqwuq5/heZbSOag7N2fbnrTPQ8yt7YdQ186spuva+pchZjTXg7rBoW1nRuZiy/dvCKEYWT1KUmGyzFCgZiVN7bj759DvLQN7L1uPUQeyc4BjXJRO18qSCFPxpK279wS1GwWZ1NWCS1pMxiBzSbe7ZN862sUEt8+dXpTpphvk+dxt2LgO6YJRju0cuiquMcWTDYY28PkBHnjxq9+Hum9ctprLmw18NtTJz37yY6i7fes9U85HOA7st+HRrtX7ffCLdyDm0/c+grrEiQKbTdw7O2uYIHjo5h7Tar71yitQN9ex59o7xD3p1oMHppzNoTZ8jrSz4XR7F5aw3ZfJvYz7tu17OzhfJjmutUbH7ovNOdwn2e/x48M9U/7be+9DTPsK6r6e7Vud4NEm6j5j0H+uhBBCCCGEEKIG9HIlhBBCCCGEEDWglyshhBBCCCGEqAG9XAkhhBBCCCFEDXzhSYRBvk6T7BKzipNKyN35I7WbIfWGFiQZX0zbfZJUBhM788S77vok8S+t88eRpMVUHB/TdzTPrrufmKysZwzrX2/0QZNSE+F/A5Kr4jJjImWfBNYnhQwhhIoIN+e6VoiaEPeDwYQkonTljNzLskvgt9TFe0lyTDS4f2gFwj2vmg4hlDFJb9lUIUY1kMCbnDsjfVe6XmCJm+naCxFmJzVywtzRzKMEEqezczcbKGROnWB+OsSEvR3Sx+01axax25zHC/aPoOq6E28/bWOCyTvH9rh2axlipkMUc19fsKYa6xuYDPjDoy1s5tiK7xtzeC9zC4tQNzq0A+ETwIcQQpqSx7EzLiC5jkMaYa50mtMzH+G9ZB3bbn59YhTRswlYj3YwSesxbjehiNg7eRtsbZ5jVMmMsVwc8XYKwT3H28QcIKmwrixn/yxbI4YBX3vlhim/2sX9/PazR1D3zmObhHbvGNd1VeK5Rs5E6LC1BDE35rDvBtvWIOAv730AMf/j/wBVJ+Yv//3/BXXTI9uGlJnCJMTQ4vljU/75v/9fIKZ8/BjqmhO7bzRbZJ+cw6TsmZsz166+CDFzbTR4GDkDjc1DNIY5Htm1dYGYpDSIGVczs3UN8vDrNMnzt23ntf9NHUIIxOMqJC3bL2kb+4mt0f6xnev3b//fENPs4TPl+YE1uTjALSgK/edKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGvjCNVcelriN4fUvXBcRcT12bnq92TEswau/QgVJUkMIwX/ryt55Sb+cOInoyTRP/tv+kmlYSELiQO/5/3+bWFLouigKloTalun4smFxOjevpfrsXAQII8ldW/gN9Py8/QY5yfHsoynqTiqXOLk7j98yL7vvwJtkfR73MbFpf+S1hkzLBFVRUxP0VSGENFghBiTYDiGkFdGLBZekNTKB91nnZGU5rn3DWCJFltzUk1F5JcsGbvs9I9/ot1L8hr05tec6T2KeFniuJ8dWC/KgPIaYQdtqGdqrqEVJKkyO2W4umHLWwL7LmjhfypFtJ9Omse0bUt5TjSfRILkj2byjCdCdpjM9xTTXvzxGUcKbbas7m2fzqSSJxXs2iW+/jwKrKUnAnrg+SKpIHXFEt3j9WgghVO55wbRwVWLnRjWHyayLBs7pzO+xpN29CUk+PD405ddvvggx37z4AtQtztl7+U/3UWu4dYj9WTrN1WCMWq3H792GuvbOXVNOCkwKXSeTfdRAzTndTrODe0SRYx9PD+z83L7/IcRcIBrkZumeM2QPZMu423HPdvL8L0hi6K0Du3c+H6CmNTTdXkYWA382uOsX+PwviAgxcz4FWYL7a05+h4299p08d8jPi1BM7Xwc7WMy4GkTx2HsfksEktw9Bv3nSgghhBBCCCFqQC9XQgghhBBCCFEDerkSQgghhBBCiBrQy5UQQgghhBBC1MCZGlrwJLuzYz7nbDOPY0JUX8PeLtlxqB7/3a37/yickLEkQuYsm51cjQmgPXVq7Nm5fNtpm2IdATz0VGfnGsDMADCfbYSpSAghTfzcJIfRRsyeYw2iMO12rMi1HKPANWsQcwwnxl9eQOFmJ7UDMxyg+PiIJJOdesE3RHxe5ewxT8iqrYK9lzRlSSFZEmF3HpqwHMG4002MnbC15qoqlsk0IlEzM6/ge6BLIjzF9ZAH7PdVlzDz4aNPIKZJhMXZhYumfL6xDjHj/lNTLqfEmCJFwXVeWhOG6RTbPSVC8ayyYufpBE0ZSmIiUrjBYh4/ZYXtrEq7tjIyzxosUTwkET69+fnTv/451C1/749M+cXzOL6dEoX/w5E13slJQvSEJGD3Bh4U+rxyIWTa02e2CywLPHA8tfc8SdCM4NIFrFuaWhOD+bkFiKla2KZ2Yvvu2fEziPney1eg7lznJVNOWzif/u6jJ1D36YGd+ynZl68s4pq92LTtHFf4/KiTl1+8DHWdtjUXKUj22mL4FOqOpvb5N56gmcuUPWfc9GDrvyBz3RttsbU+LbH/Ws6s4uoyJlc/btrn/WBEztPC+0tS286SGHiw/sy8yQ75OTUh5hi5M/pJCnI9slf78w9Im8jPojC3smrKJUksHoP+cyWEEEIIIYQQNaCXKyGEEEIIIYSoAb1cCSGEEEIIIUQN6OVKCCGEEEIIIWrgTA0tuFjcK0ojhbcn9Tpw5+eeCUw8btVxFRHQMsOD0meXJmm4vZcCEx9X1LADGkCISLFNjUbIWPk6n0k+hJCyNOPu/DHmHL8N/J3nqZMY8wxmpMDNDpxwkvRTFUiWcT83ybmZuLrwdU08MuvgUl+ct0LphTbGjMdW0HrURwH/eIIC0yr4MYeQwO4wcWJgdr/8OCsMrwIRSSdEQQuLJvZ6MfdXH2z9e+OUlIidKyKSDs7AgvUKNRJwKuxmhmL8cooC6F5v35RXzr8AMeM+Cpnb3Y69foL31w5WfNxuYLtX5rCdw8TO2eOdbYjJcjzXYsuaFIwHxxDT6x9Bnd+72DaZETOQsrJ1VYETLc2wX/w8LpiCvib+0SL2wTs//3NTTr/zDyDm5aU21FWVHat2C/fcNlHCH7vnrJ/jn9Wxme6MP8gaSpnLhTtXQfb4Ztfey4svnIOYFzdWoG518bwpd+YW8frkz+Kl65ekhe1udvH+lrvWdOIHxJxjtIf76c6BNXyoMmzUNMfnxdOdXXueIc6fOvlX//RfQF3vyF7z4aNdiDnY6uNxfdsPJRn3pIHP0cT1DdtfR8Qsat49W6sWGsP0R7hvdLt2X7ya4Ry6/clDU949xHFYXpqDumbDzqEJ2Sd7Q9zPM7e29of4rOi0iSGRe0INenhcPsXreaOmLvl9E8j+0nfPsMGE7Ruz0X+uhBBCCCGEEKIG9HIlhBBCCCGEEDWglyshhBBCCCGEqIHfuyTC0V+GQ2Dkke5jd5ack2mCQA/DYkgbIGkx005FJDKsyDfzvgns+1/WK76dNAEzuT+vHwskWR5PPupjWOXZJQzmzJ4/VFfj9VUhhMIlwmui5IPfLgw8GU+SKLZw4zLXxu/qz63gt9Othh2/Yorf1R8c24SPvTFen+mBmm5q5Dl+E12wZMCV/aacJ7idTZKQfqpI8kGfGJucq2Lf1bu2n3bCa6o9c1Up2SOYxtMnXGX3zKRaZW77tJHh9//5mHx/f2i/YR/mmJwzS1B7Mpla7VLVxDFtJVbTcWllDWKaE3zM7bp5XQx2IGY+wePmE5uM83h3C2KGQ6xLXbbKymcVDSGMSRLPzPV5xuYZ08emfoxPT3N18ztvQN3w794z5cPffAwxR6+h9q7dttqQDaLL8kmpQwjhYGjn3SRSlA3PQqZ3JscllddckuTuXTt/Xn4JE/hmRM/R71kNzdP+IcQck7U+8Jq9eVyfr7RQe3PVJYrPSULW7SPUA01Te/7logcx+0ePoG50bLVMBdF41cl3br4Edb2956ac7mHb3+3ggzsDfSPOxTTDfSNzOqxyis+iwTFqnhZ7dg+cjlFv9OwANZ7trt1PGxN8/h4e2z2vmOtATLszD3UL8/Zc+4eoTXu2g/tp37V9a4TH3Vy9BHVhaPf4/h7q46akPztrdq/OuvgbaHvnAOsKe70B0ZTHoP9cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGvjCkwj7ZKMnzw6Mx7G8iZgQkLxfEpOC0hkJYLsDdSnwiS99klQG066z49LMJYokZgeQ0Pazk/kzQYi/3xBCKKFDiSEBuz9IwIwhXzRU9w8Vs5NLhxBC4cwbmiUKhDMili994l02LmRSF7mty+bQ0KKZETOZ0o7xqMB5lw3kAAAaV0lEQVR2Bpf4b2EBRdIZ6bzcCWj7A5xPRDeNBhYkWXcIeK7UJYVNChShTolLA8nJCpAhDokTgZ/2nGZ7me+qkqUDpm3384yMHxPM57ZPu90uHkfmwuDImU6cwzk0bOCcPXDJHNfJXnZ51SbCvnB+HWKSEkX8h609U56OUEy+kpNOd0lEhwco3B4UKDBPm9aYYZwTw5Up23PtABIfjNBgRlEusWfuzYhqpNW+CXWv3rB9/svb70LMnV0U0L+1fNGUz69izNUlnHdPe/b+pvQhSn7unDRRvetPtnX6RdupcI7//IOHUPeLj6whytYRmhEcEwON5QtWsP/t19EwpNVBUf+DzU1T/qtf3oWY+ySJcKNlDR9euIDjstZAQ4Th4uumfO4itrNOPth8AnUXmnbAXnntBsRcu3cH6h5uWSOMPjFSOCDJ1TsNVzfB/hwf7kPdYNfuGz22vxKTqa1daxYxJMnO09S24fLyeYg5N49GQx23ZvIJTv79Hu6B08K26cbaEsRcX8b9Oz+0e+z4GA1eqPlX0673oym2c6uP47c3tustJb+dYtB/roQQQgghhBCiBvRyJYQQQgghhBA1oJcrIYQQQgghhKgBvVwJIYQQQgghRA2craFFhFkFi2BacV8XKznzphoJE7AygbBXtZcoIkwge3cIWWq7mF6P3qFvEh6Xpvbd2AvVPzs1njupvBifmCRQAbTvO9ZQ1gRfeUL1/ykmci+Z2QrMFfxbBBgwhBDK3ApFixyz22ctFL3662G/hZAQRfvUCe+ZDr9J+tyfv9lqQ8y5thVA+7kTQggFEefuubqKGFOw6QptJO32ZhIhhNAITpiaY5smxETArw+6PklDT7r/nBS2YrznBBsb1rLMjXtJHDum5LijiTWmmO8Q4XYXzSomQysk7m0/gpj5q9egbmPJCp4X59GYYmHRGlokbRTVlwHbtOwMJoZHKLwf7G5BXW98YMrHR3sQMyGToXTPhskEhdQVmZ8x84rupn4en6LhStrE597iRTt2rad43K9vfwJ1l7561ZSX1nFPunkR6z7ctePSHxHDIGaO4/uJdjjZh93fpSfE2KBwe9DR5nOI+eWvPoW6d7fs86KaYv9Wczhfv3TusinfWFqFmMMnOF9/9ov7tk2baH5wSAw7zq/YtXbl3AbEfPnKD6HupRe+asrXvnQdT14jj0f4LLhy/UumfP3yqxDT/Rs0YSmTW6Y8mgwg5oD8ql5ruWdtjnNxOuxD3fG2ndfJ8jLEzDXIudzWnC6jecT6oh2vlzbQ0GKug+duJm7PJWtmeUx+86QXTHnVm3yEENIhHnfvoTV9mY5xMjbbuCd0l+383M2xf/s5rlt/O3PkOReD/nMlhBBCCCGEEDWglyshhBBCCCGEqAG9XAkhhBBCCCFEDZyp5orqGWLECzFaAiadimgT0xt5LVMIIVSlT4SLOgWmhyndDbKEq75fWD/xxMI2jr0p07y3wd8LfsNK7w/aSfRG5DjM00j6l2nDfLJTls21LliWVgeV57FTuQS2+RgT6jVbLBmv/W64JPOJ6bBylxxvQr5JLhPsO5+QuCCaj9xl+vXlEHgSwdHEnqsg/cvntG1nQhIGZySZbFXYb999IufPxQ3qSaUpp50Xm85814FppPLLr1Gma5uSGzpwiaHbQ9RmXOqgFqTRtHN9f38bYoYJjtfyhtNiJER7ktrv4csxNjyv8Fv7yciu0d4OJvDs76Hman/T6sXyEWoEAtEu+gSWwzHqQFIyyI3M7pUpezbgYajfJDGnitvfvv7lr0JI5xlqWv7q735qykskYfDGRdSPXNq06/9gE/ekAUv0W/ln2uyYEDCZ82RCEpS7zMLHewcQMzwi2ruJ04GSJmVkH37ywCbL/bdbzyBmcITzfH/XzsXBhMyWDq69Sy9YDc3rN1BzdX4BNUk3X3TasOuYOLZO9g7w+dtzyY3L9YsQ03zpS1A3/E8/MeVigut/SHQ8U68Jml+AmHIwhLrjQ7vHzqc4DgvrmOh3xSXobRCN3uKS1bB222R/Jc9fnzx6eQm1sEslJqtOXWLz4gCTAT++cxvqxnu7psx+Oy1cXIO6idNKDQZkryZjteTG6tIF1APHoP9cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGjhbQ4voShdCVaYxF2SGALOlvTHmEcxcoWSJhf25SCLDzL3jsmTL1AsEEv2SBK8FaacXtLOEwSyXqjP6qJgJBB2q2UmL6ajEJHitiZQlivWicHq/s81WiikKVccDYnLRtaLMRorJ63Iy74ZDe35m5sB6zguui5yIsiOMXLgJjV8vManA8a89SYX3kpZoBpBPnaFFgUJVmgyUjp+DmsKcMRH7FiUurzhQEhH/0O0lR2Mcm06Cj5T5ZseUmwnO66O9HtRNxtY8or+NCVA7XSvUTjK8/pTsb32XWLR3hOuRrtuhnWdZC4XbQ5Kruj+09+dNb0L4HLMKt+cQj5tQRczhU01yTbdAO8Zzi2gYsE6MDD750V+Y8tEUxfKdDAX8N9bsuB8c4iB8OiBmJ4V/NkEITx7v4liSdG/ik09wvVQk43vqn5cJ3ks5RZOWrcd2bj5nz0vyGwV+D6QYs7KC8/ztr9w05e+/iklo9w/vQd3B2F7vTg+v9/UVNFc4KQ8ePIS6m9etWc0rr+H4XSAmEPNufzkO2M6C7IGlM/pJm2hoUaW4B+Y9287eAe6BbHW33JOUeFWEzG1vVYlGEYzUzZcm+V006uH8PNreMeXtx48hpreHJhetpu3PC1fPQcz6zRtQV120RhSLx2hoUabYzq+++ZYpLyycLMm1/nMlhBBCCCGEEDWglyshhBBCCCGEqAG9XAkhhBBCCCFEDejlSgghhBBCCCFq4EwNLZjylZk3nARmdhAj3I6ViSfuPTQlr6UlEfZ5k4uKCEp9snVu3BAhxmdGETGdQK7H2uBvj1oUkOvhuUjM72rf77rgKZK4VrHLM4+LELxhCAZNxyhe9cPZ6i5jjDMHCAHNG0ajHGIqYlAAnc6MG1wd9a5gc8ybkdAxJ2Luyt5LUg4gpszRaKCYWoOCaNMUaBOrnO0KUZ3y5GTybm+AQMeGtcsL9CONYnyX9nPcyzYnaDay7sT+a+02xDSJecvk2K6Rgoik+4ntGWY+MC3Inus28CExmJhWeNy0ZdvZJ+cejogJS27P32DPDzKC3iihJPM6ZcvPnao4XUuL2ZAHZnORGPbsPzDl996/DzHTDppjvPbSN0z5pStowDB9hIL25yPbhjFzDAloiAKPXmJMkTizjDTBVcz3xcKVEbafe7MhtqwLYkjUyGzd4hzO6QudA6jbaNjnzAuX0WigP3oAdQfOWGQ0Pt29c3tnB+r2HlmznHKAe8uba2iccrFt58swQxOItIlzr7lkzVvOX30TYs7P4fN+6+7PTPno4W2I6e9sQV3eswY9/Xk00GjPW5ONRou8DpD9tCztuOdj3DuHR8dQNziwc2g4wj5vt/F61158zZS//cf/EGK+8c//CdR1L1tDC+pHlmDbG/43Vom/uWLQf66EEEIIIYQQogb0ciWEEEIIIYQQNaCXKyGEEEIIIYSogTPWXJ3ed98nzbFJz8XaCVVEp0QS0YL2JKadVLdE4nyCVxbEEiAmv7v8OU2Ar8Njuxy+BafzgPQnJFM8zW+zyTfsUKYf7WJdjNavYIlw7bfuPrljCCG05pegbq5pNSx5gW0alyTJpWunT17525bOKH+ObsCNVSPFe2kGooWZWI1VnpPEilPsO9QgxO012PbZ84CF8TldHyzBLNwx1UnG6OEQsm1AG1DZx3VYzdR+154VePJ2E/U3acNqVMoUNSupT8DOdK8ZHlc17KPPXysEPq/HLkH3cY46HjbX206rxSSQORmridN05VPS60TH60/FtaF1MVvry8Yla6H27lzLalgax6jd2D9CncTOSy+Z8is3MUHxKunzXzyxe8nWAOfBiCSF9r8RBofYzp2ndszzMdEVsokA84AkbqcqTHuukhzXbOA4rC/acbi+jDFzYRPqqt3ntqKD6zrDPLxhvmXP3/ai8xBCnT9NpyPU7R66ZLy9HiYRv3TtKtQtLtmk1o1DfBalbUx8feVVqwl8/RuoG7p4fgPrbtoEtoPf/DXEfHLrl1C3+XTbHtfD5MONdN+UM6bRI2u7dHtSQfb8qsAxnbpk2OUaTo6r19ag7s9++Kem/OV/8d9DzPyVC1AXnI7Wa9NDCCFroq4ueE3ZBPf4EGYnXNZ/roQQQgghhBCiBvRyJYQQQgghhBA1oJcrIYQQQgghhKgBvVwJIYQQQgghRA2cqaFFVBLPyISWETr0KCU6T7I7OwEpOyolhhZe6B5zewkxMmBUTnXOEmjShjqzAWbUQIXwJwTHlCVAZImMIaq2NuH1Z5tVxIxvCKzvSOJPOlZ23IsJimyHBYpzQ7dris0mCkXnW5jY0C//hEw7MHdhySvJmScjKwJNK2z3dILJgKdOsO8TFobweeJ8Z9IQ40kT2LhHmpacMXR6pn4vizzQG1pkOBfTiKTTbM1mGT5SCmdWcUiMKTKSYLXpDA9aDRQRZ86sgt1uWbKJ7bNjs3mNJ2uVtk2r7S7EMGF4w91zSvqA5KENez1r6DI+2IeYkojHwYyDZb2vC+bJkNs+7w2xjSMyV+bXbSLaZhuTn2ZDFJgnfZsoNksx0fDFFzAZ6N93Bg8f7OC43D7Gto8H1tjkzsNPIWbvyCaqzYeYNHV7hIYIUdndE2Ii4A5LicHEy6v4HHh50R6YpZgweG8PE/F6g4C0jeP52qs3oS4PNllud+FkSVpjYc/aVtslHyfP9oVrL0BdZ3nVlLOnaBTRbOHz9+K1r5nyjTcxifD0GNv5pde+b8/zzTcg5tZf/Buo+/H/83NTfr75HGLKiTVhqXI0fCjI3lm45OrEPyusLOI8W9mwe+f5b34ZYr725peg7q3v/YkpN5h5BaGY2vVWVcSYIsG5V/YOTfnhAzQReenr/2zm9fWfKyGEEEIIIYSoAb1cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQNnamjBzSpmmxSc9LiomNhzR4naY0wZZh/FTBLYiXwcu9uSmWPEiPijiDsOLhfpNnB69hWEiHFKSbvZXyf8uMQYMLCqJODYVQXWTQa2rsomEJM1elDXyKzRABP++ltmRid5Qe7FGVPkJRpa5AW205+KGY3QoWIGITXBruf7AYw/am8Ent/3VUL6ipkyYFDcfpe6e+w20WBifWUN6pbXbV1BjAwCMbRIUhvXJMdlzhiiTEgfEFG2168zg4mUmEBUwRlokDWaEXF86u6lTPBejge4HnrVUxeE6zgEPM6POzXQqQm2Rqelvz7GzJNpsNa1c6rbxHEZ7aMw/c6775tyb/sQYq5dPgd1y40lU35hfQNiusttqBsfWFH/cQ/3t8Mta1bRK4hhQIV1DbcW/D4dQggrXWzT6qLtu5V1NFtZqrBfOuWmKR8dbUNMQvb4VtMOoF+LIYSwtHQJ6qIetjVybgONKa6+8IopLyyuQMyQzNnGgjVYqSo0FhmPyToe2b55/AzP3T1Cg6dX3lo35c4+zrPKzeEQQlh98UVTPm7hXGi5YWhM0XClLNFw5XBgjTDaK1ch5psvfw3qfvBntq79Bq61uS5er0Hn0GzShjXVSHJcR/n2M6g73H1oynff/VuIkaGFEEIIIYQQQpwRerkSQgghhBBCiBrQy5UQQgghhBBC1MDZaq4ikvMyTpzP9sTJP2drT06apJR8xhuXyJQmA4YTQQjTCfmw2O6N0m/QA/1xLEnybJ0ZTZJcE1zbY+sK/Lw6lHROz54sMTIXNp9YssOm04Z0Aja0MSWJRqf2G2+uZXK6PpbstYMJA7suAeygjzqJopydSJn33ezEuFT/SJM5Q2ZciCm4aG7mueukYHqqCI0ebZe7Z3Zupt/yD4vlNmqurp9DzdWlm6+a8photWLWdsr+FljZugnRQOQlahm8LqpF2tTMUNeSpjauIGuN3YlfN8cotQmjbUzemu3bROIp0d/4ZPIh4LKha6YmSqYDza12oplh/y6muG9cXbY6jPX5ZYiZa6PuZDSyY3y4i1qKxQWiveta/cjh9m2MCYtQ95LTmZSLmOz4MLd77i7RXPWGmCjeJ2Bukb5bJknhLyxaXc1ciufOJ5iEejC2dVWJ7czIWkjcjsCm2GCEfd539zxyGp4QQrh2BXVSJ+X1r3wT6m689V1TTudxjBPSrnbHJp1NyZ476mG/3/vNB6a8uHAdYv74W69C3e6R1UH9+p37EJN1cM/tnrfJjhfImM4v2ETbWQNjOh383XD+2M6X1699C2Le/pN/CXVrr7k5m6F+tCweQ11IY15TyLPP6QQnT1FTdrD5IdQ9enbHlJ9u4ZqJQf+5EkIIIYQQQoga0MuVEEIIIYQQQtSAXq6EEEIIIYQQogb0ciWEEEIIIYQQNXCmhhYnJU6MGyfY9QmJWYJimsTX1SVEOF2RhL3oVTHb1IPfCROdzz4uYeYccGomiMazYeJUxskSKXMTD3+9s00UG2O/EuMzwsSWPOmsrUuJeQUztMjc+VH+HEKDznNLSdpUpFZA35nHZIvzayioTVyC4OkYReiDKSZb9OuRrf24lc7MHZg5xuzJyYxc/LlOOy1mwdxUAGLYweYQHBZjEIKGGc0Gxqyt4PxYWbWJMIt5FP8nJGGvr6mIsch0bOt8gssQQgg5zrPgkre223j9RSJy94kpqwTnGUvcnpe216dTYkzTI4YLzkCDJQMuyBj7eX1iM6IIjg5QmD6a2HHIiCg9HaLRyFzLGgYsdfF+swrHs1FY4X1B1n+6gCYQc24edAtMsvt4dxPqnj/52JSrtAMxZWbbzoxjpmRu5m5fLEkC38fkmb21YZOtvnzlIsQsNGcnvS4aaJqSFTh+o7GtGwzREOHhg3eh7vHmc1MeHuGa/e/+2/oMLW5efxnqNi66xLfs+UjWWiOzpiEZMZgJU7yf0dF7prz37ALE7B9gMuBbW7+w52mh6c2rL16Gul7/lilfbeD87K7Yfbmaw+vfuHkD6qZ7j0z5q9e/DDFrr+EeHzLfnyTZehbzJCW/vUe4bqdPbDv3nz6BmL0dXNu37t415Q/ufRTRJkT/uRJCCCGEEEKIGtDLlRBCCCGEEELUgF6uhBBCCCGEEKIG9HIlhBBCCCGEEDVwpoYW1JgiQsDOiRCUE5GiNxJIyftlGmWuQATzJdb591cq3CbCSbg8rbTXIx4U1GQjpu8SNg6u7SW93xqF077P6b3UAxOvwvUiTCFCCCGNcPAg2nyY+6x7E9q/to6ZXrCGVn7tZSh6bS9Z0eucE8GGEEKjg9tINXSZ3dnkZAYhrg/o/dL+jejzCGMKCmuCmy709k4Z7CuEziEX6AXtn51rtsVLCgLlELIm1rW71pRh3CIicDKm06kVyJdlDjFVZstpSvZlsrZb7XlTbjbnISaEDKtcX1UJxiSkDg0myLMpw+OyzK4ttrfkZK/Gvfn0JuiDZ8+xcmIF5g1mkDTuQ93xcGTKRRhHHRecYUia4BxjYzVNXbtauAd2uiigL4Kdm9McTT2qidvPiSlNOSVzemrvuchJDJs/Izen00sQ02jgXl263zLEpyYE0p/T3NaNc1x7vb37ULd5/6k7jqyzGulOsP/ajdnXrKZo0DGdWBMW9oskL/C4vd2Hpvz82QcQ8/5v2lB3YdHO9W9dPAcxF4npRKf/zJRXyYMg6W7YivNXIGbjCtZt3rX92bqEvwnYA3F0tOtqcB13FnD9hdStm9EOnvvhJ1BX7Np5tr39AGLeuYPH/fIjawayfbSPbYpA/7kSQgghhBBCiBrQy5UQQgghhBBC1IBeroQQQgghhBCiBr7wJMLREiuH/+KYJQPmCV69xoudPSYxJEnYSb6ZT10XsxivN2CSEqZFK8sITRJLdly6OtoJRIdR+e/a8d2cJdA8Mb5f6jszUJBvkiHxJukmpldhyh6oiUjuSvWHTP/jtC9cB8aSj1otTHMJkwEvrJ+352nhd+FJgt+YFzDvmBaGNNR3Oe2C2fOVa9PIuSLEUkwn6dtwmklaP2sESxTr28A2DqyC5Lwkhq1jf36v1fjs5KQus3MhbWE7vUQvhBAOJ1Z/k4ww6WyY2ISreYEnysj4NRI7j6dE9zEpSPLhoa1j67gzT/RbLtloxTQQLOF74tc225fJs8itP66PrYf9fUxsmk6tnqIi2qJ8guM5nrg5RpKfNhL82TJ1z6b+EPtknJPn1ZxNCtvo4ti1UfYVqsT2L3t+lK5NOdFc5VM8+WRk728yxpiUiHYXOvZe2kRflXmNWQihcusjJeslI3NzWtq6PslzfniAbe/tHdlyebo/QzP6g8qPF3k+TlBHt7Zq94kk4LOvKvFceW7n8XCCuqHBCBPanrv5D0z5xa+jvqq7hGtkYcFqsxpMhu2SRScdPE9C5svcmk0U3+gSnRR5rub9LVdDJkwbNV7FwGqnjp+hjq+3iWPVTu3Y3H30G4h59w7W7fbsc2dSnEwTqP9cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGkjik/YKIYQQQgghhPg89J8rIYQQQgghhKgBvVwJIYQQQgghRA3o5UoIIYQQQgghakAvV0IIIYQQQghRA3q5EkIIIYQQQoga0MuVEEIIIYQQQtSAXq6EEEIIIYQQogb0ciWEEEIIIYQQNaCXKyGEEEIIIYSoAb1cCSGEEEIIIUQN6OVKCCGEEEIIIWpAL1dCCCGEEEIIUQN6uRJCCCGEEEKIGtDLlRBCCCGEEELUgF6uhBBCCCGEEKIG9HIlhBBCCCGEEDWglyshhBBCCCGEqAG9XAkhhBBCCCFEDejlSgghhBBCCCFqQC9XQgghhBBCCFEDerkSQgghhBBCiBrQy5UQQgghhBBC1IBeroQQQgghhBCiBv5fjoop48flRNUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x432 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "%matplotlib inline\n",
    "\n",
    "# show image of 10 random data points\n",
    "fig,axs = plt.subplots(2,5,figsize=(15,6))\n",
    "fig.subplots_adjust(hspace=.2,wspace=.001)\n",
    "axs = axs.ravel()\n",
    "for i in range(10):\n",
    "    index = random.randint(0,len(X_train))\n",
    "    image = X_train[index]\n",
    "    axs[i].axis('off')\n",
    "    axs[i].imshow(image)\n",
    "    axs[i].set_title(y_train[index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.          0.97674419  1.95348837  2.93023256  3.90697674  4.88372093\n",
      "  5.86046512  6.8372093   7.81395349  8.79069767  9.76744186 10.74418605\n",
      " 11.72093023 12.69767442 13.6744186  14.65116279 15.62790698 16.60465116\n",
      " 17.58139535 18.55813953 19.53488372 20.51162791 21.48837209 22.46511628\n",
      " 23.44186047 24.41860465 25.39534884 26.37209302 27.34883721 28.3255814\n",
      " 29.30232558 30.27906977 31.25581395 32.23255814 33.20930233 34.18604651\n",
      " 35.1627907  36.13953488 37.11627907 38.09302326 39.06976744 40.04651163\n",
      " 41.02325581 42.        ]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist,bins = np.histogram(y_train,bins=n_classes)\n",
    "print(bins)\n",
    "width = 0.7*(bins[1]-bins[0])\n",
    "center = (bins[:-1]+bins[1:])/2\n",
    "plt.bar(center,hist,align='center',width=width)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RGB shape: (34799, 32, 32, 3)\n",
      "Graysacle shape: (34799, 32, 32, 1)\n"
     ]
    }
   ],
   "source": [
    "# Design and Test a model Architecture\n",
    "X_train_rgb = X_train\n",
    "X_train_gry = np.sum(X_train/3,axis=3,keepdims=True)\n",
    "\n",
    "X_test_rgb = X_test\n",
    "X_test_gry = np.sum(X_test/3,axis=3,keepdims=True)\n",
    "\n",
    "print('RGB shape:',X_train_rgb.shape)\n",
    "print('Graysacle shape:',X_train_gry.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1008 with 80 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_train = X_train_gry\n",
    "X_test = X_test_gry\n",
    "# Visualize rgb vs grayscale\n",
    "n_rows = 8\n",
    "n_cols = 10\n",
    "offset = 9000\n",
    "fig,axs = plt.subplots(n_rows,n_cols,figsize=(18,14))\n",
    "fig.subplots_adjust(hspace=.1,wspace=.001)\n",
    "axs = axs.ravel()\n",
    "for j in range(0,n_rows,2):\n",
    "    for i in range(n_cols):\n",
    "        index = i + j*n_cols\n",
    "        image = X_train_rgb[index+offset]\n",
    "        axs[index].axis('off')\n",
    "        axs[index].imshow(image)\n",
    "    for i in range(n_cols):\n",
    "        index = i + j*n_cols +n_cols\n",
    "        image = X_train_gry[index + offset-n_cols].squeeze()\n",
    "        axs[index].axis('off')\n",
    "        axs[index].imshow(image,cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([25.66666667])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train[0][0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Normalize the train and test datasets to (-1,1)\n",
    "X_train_normalized = (X_train -128)/128\n",
    "X_test_normalized = (X_test - 128)/128\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape in/out: (32, 32, 1) (32, 32, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cv2\n",
    "def random_translate(img):\n",
    "    rows,cols,_ = img.shape\n",
    "    \n",
    "    #allow translation up to px pixels in x and y directions\n",
    "    px = 2\n",
    "    dx,dy = np.random.randint(-px,px,2)\n",
    "    \n",
    "    M = np.float32([[1,0,dx],[0,1,dy]])\n",
    "    dst = cv2.warpAffine(img,M,(cols,rows))\n",
    "    \n",
    "    dst = dst[:,:,np.newaxis]\n",
    "    return dst\n",
    "\n",
    "test_img = X_train_normalized[22222]\n",
    "\n",
    "test_dst = random_translate(test_img)\n",
    "\n",
    "fig,axs = plt.subplots(1,2,figsize=(10,3))\n",
    "\n",
    "axs[0].axis('off')\n",
    "axs[0].imshow(test_img.squeeze(),cmap='gray')\n",
    "axs[0].set_title('original')\n",
    "\n",
    "axs[1].axis('off')\n",
    "axs[1].imshow(test_dst.squeeze(),cmap='gray')\n",
    "axs[1].set_title('translated')\n",
    "\n",
    "print('shape in/out:',test_img.shape,test_dst.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape in/out: (32, 32, 1) (32, 32, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def random_scaling(img):\n",
    "    rows,cols,_ = img.shape\n",
    "    \n",
    "    #transform limits\n",
    "    px = np.random.randint(-2,2)\n",
    "    \n",
    "    # ending locations\n",
    "    pts1 = np.float32([[px,px],[rows-px,px],[px,cols-px],[rows-px,cols-px]])\n",
    "    \n",
    "    #starting locations (4 corners)\n",
    "    pts2 = np.float32([[0,0],[rows,0],[0,cols],[rows,cols]])\n",
    "    \n",
    "    M = cv2.getPerspectiveTransform(pts1,pts2)\n",
    "    dst = cv2.warpPerspective(img,M,(rows,cols))\n",
    "    dst = dst[:,:,np.newaxis]\n",
    "    \n",
    "    return dst\n",
    "test_dst = random_scaling(test_img)\n",
    "fig,axs = plt.subplots(1,2,figsize=(10,3))\n",
    "\n",
    "#print(test_dst.shape)\n",
    "#print(test_dst.squeeze().shape)\n",
    "axs[0].axis('off')\n",
    "axs[0].imshow(test_img.squeeze(),cmap='gray')\n",
    "axs[0].set_title('original')\n",
    "\n",
    "axs[1].axis('off')\n",
    "axs[1].imshow(test_dst.squeeze(),cmap='gray')\n",
    "axs[1].set_title('scaled')\n",
    "\n",
    "print('shape in/out:',test_img.shape,test_dst.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape in/out: (32, 32, 1) (32, 32, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def random_warp(img):\n",
    "    rows,cols,_ = img.shape\n",
    "    \n",
    "    # random scaling cofficients\n",
    "    rndx = np.random.rand(3) - 0.5\n",
    "    rndx *=cols*0.06\n",
    "    rndy = np.random.rand(3) - 0.5\n",
    "    rndy *=rows*0.06\n",
    "    \n",
    "    # 3 starting points for transform,1/4 way from edges\n",
    "    x1 = cols/4\n",
    "    x2 = 3*cols/4\n",
    "    y1 = rows/4\n",
    "    y2 = 3*rows/4\n",
    "    \n",
    "    pts1 = np.float32([[y1,x1],\n",
    "                      [y2,x1],\n",
    "                      [y1,x2]])\n",
    "    pts2 = np.float32([[y1+rndy[0],x1+rndy[0]],\n",
    "                      [y2+rndy[1],x1+rndx[1]],\n",
    "                      [y1+rndy[2],x2+rndx[2]]])\n",
    "    M = cv2.getAffineTransform(pts1,pts2)\n",
    "    dst = cv2.warpAffine(img,M,(cols,rows))\n",
    "    #print(dst.shape)\n",
    "    dst = dst[:,:,np.newaxis]\n",
    "    return dst\n",
    "fig,axs = plt.subplots(1,2,figsize=(10,3))\n",
    "\n",
    "axs[0].axis('off')\n",
    "axs[0].imshow(test_img.squeeze(),cmap='gray')\n",
    "axs[0].set_title('original')\n",
    "\n",
    "axs[1].axis('off')\n",
    "axs[1].imshow(test_dst.squeeze(),cmap='gray')\n",
    "axs[1].set_title('warped')\n",
    "print('shape in/out:',test_img.shape,test_dst.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape in/out: (32, 32, 1) (32, 32, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def random_brightness(img):\n",
    "    shifted = img+1.0\n",
    "    img_max_value = max(shifted.flatten())\n",
    "    max_coef = 2.0/img_max_value\n",
    "    min_coef = max_coef - 0.1\n",
    "    coef = np.random.uniform(min_coef,max_coef)\n",
    "    dst = shifted*coef - 1.0\n",
    "    return dst\n",
    "\n",
    "test_dst = random_brightness(test_img)\n",
    "fig,axs = plt.subplots(1,2,figsize=(10,3))\n",
    "\n",
    "\n",
    "axs[0].axis('off')\n",
    "axs[0].imshow(test_img.squeeze(),cmap='gray')\n",
    "axs[0].set_title('original')\n",
    "\n",
    "axs[1].axis('off')\n",
    "axs[1].imshow(test_dst.squeeze(),cmap='gray')\n",
    "axs[1].set_title('warped')\n",
    "print('shape in/out:',test_img.shape,test_dst.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# histogram of label frequency (once again,before data augmentation)\n",
    "hist,bins = np.histogram(y_train,bins=n_classes)\n",
    "width = 0.7*(bins[1]-bins[0])\n",
    "center = (bins[:-1]+bins[1:])/2\n",
    "plt.bar(center,hist,align='center',width=width)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 180 1980 2010 1260 1770 1650  360 1290 1260 1320 1800 1170 1890 1920\n",
      "  690  540  360  990 1080  180  300  270  330  450  240 1350  540  210\n",
      "  480  240  390  690  210  599  360 1080  330  180 1860  270  300  210\n",
      "  210]\n",
      "minimum samples for any label: 180\n"
     ]
    }
   ],
   "source": [
    "print(np.bincount(y_train))\n",
    "print('minimum samples for any label:',min(np.bincount(y_train)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X,y shapes: (34799, 32, 32, 1) (34799,)\n",
      "X,y shapes: (46480, 32, 32, 1) (46480,)\n"
     ]
    }
   ],
   "source": [
    "print('X,y shapes:',X_train_normalized.shape,y_train.shape)\n",
    "# input_indices map to output_indices\n",
    "input_indices = []\n",
    "output_indices = []\n",
    "\n",
    "for class_n in range(n_classes):\n",
    "    class_indices = np.where(y_train == class_n)\n",
    "    n_samples = len(class_indices[0])\n",
    "    if n_samples < 800:\n",
    "        for i in range(800-n_samples):\n",
    "            input_indices.append(class_indices[0][i%n_samples])\n",
    "            output_indices.append(X_train_normalized.shape[0])\n",
    "            new_img = X_train_normalized[class_indices[0][i%n_samples]]\n",
    "            new_img = random_translate(random_scaling(random_warp(random_brightness(new_img))))\n",
    "            X_train_normalized = np.concatenate((X_train_normalized,[new_img]),axis=0)\n",
    "            y_train = np.concatenate((y_train,[class_n]),axis=0)\n",
    "print('X,y shapes:',X_train_normalized.shape,y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# histogram of label freguency\n",
    "hist,bins = np.histogram(y_train,bins=n_classes)\n",
    "width = 0.7*(bins[1]-bins[0])\n",
    "center = (bins[:-1]+bins[1:])/2\n",
    "plt.bar(center,hist,align='center',width=width)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "# shuffle the training dataset\n",
    "from sklearn.utils import shuffle\n",
    "\n",
    "X_train_normalized,y_train = shuffle(X_train_normalized,y_train)\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# split validation dataset off from training dataset\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_validation,y_train,y_validation = train_test_split(X_train_normalized,y_train,\n",
    "                                                             test_size=0.20,random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ora/anaconda3/envs/tensorflow/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "EPOCHS = 60\n",
    "BATCH_SIZE = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /home/ora/anaconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use the retry module or similar alternatives.\n",
      "done\n"
     ]
    }
   ],
   "source": [
    "#我们首先实现超参数\n",
    "from tensorflow.contrib.layers import flatten\n",
    "\n",
    "def LeNet(x):\n",
    "    # Hyperparameters\n",
    "    mu = 0\n",
    "    sigma = 0.1\n",
    "    \n",
    "    #Layer1: Concolutiona 1 input :32x32x1   output:28x28x6\n",
    "    W1 = tf.Variable(tf.truncated_normal(shape=(5,5,1,6),mean=mu,stddev=sigma))\n",
    "    x = tf.nn.con2d(x,W1,strides=[1,1,1,1],padding='VALID')\n",
    "    b1 = tf.Variable(tf.zeros(6))\n",
    "    x = tf.nn.bias_add(x,b1)\n",
    "    print('layer 1 shape:',x.get_shape())\n",
    "    \n",
    "    #Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    # Pooling input=28x28x6 Output = 14x14x6\n",
    "    x = tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1],padding='VALID')\n",
    "    \n",
    "    #Layer 2:Convolutional Output = 10x10x16\n",
    "    W2 = tf.Variable(tf.truncated_normal(shape=(5,5,6,16),mean=mu,stddev=sigma))\n",
    "    x = tf.nn.conv2d(x,W2,strides=[1,1,1,1],padding='VALID')\n",
    "    b2 = tf.Variable(tf.zeros(16))\n",
    "    x = tf.nn.bias_add(x,b2)\n",
    "    #Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    # Pooling input :10x10x16,output=5x5x16\n",
    "    x = tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1],padding='VALID')\n",
    "    \n",
    "    # Flatten Input:5x5x16 output=400\n",
    "    x = flatten(x)\n",
    "    # Layer 3: Fully Connected Input = 400 Output=120\n",
    "    W3 = tf.Variable(tf.truncated_normal(shape=(400,120),mean=mu,stddev=sigma))\n",
    "    b3 = tf.Variable(tf.zeros(120))\n",
    "    x = tf.add(tf.matmul(x,W3),b3)  \n",
    "    # Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    #Dropout\n",
    "    x = tf.nn.dropout(x,keep_prob)\n",
    "    # Layer 4:Fully Connected Input=120 Output = 84\n",
    "    W4 = tf.Variable(tf.truncated_normal(shape=(120,84),mean=mu,stddev = sigma))\n",
    "    b4 = tf.Variable(tf.zeros(84))\n",
    "    x = tf.add(tf.matmul(x,W4),b4)\n",
    "    \n",
    "    # Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    # Dropout\n",
    "    x = tf.nn.dropout(x,keep_prob)\n",
    "    \n",
    "    #Layer 5:Fully Connected Input =84 Output=43\n",
    "    W5 = tf.Variable(tf.truncated_normal(shape=(84,43),mean=mu,stddev=sigma))\n",
    "    b5 = tf.Variable(tf.zeros(43))\n",
    "    logits = tf.add(tf.matmul(x,W5),b5)\n",
    "    \n",
    "    return logits\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "def LeNet2(x):\n",
    "    mu =0\n",
    "    sigma = 0.1\n",
    "    #Layer 1: Convolution 1 Input :32x32x1 Output:28x28x6\n",
    "    W1 = tf.Variable(tf.truncated_normal(shape=(5,5,1,6),mean=mu,stddev=sigma),name='W1')\n",
    "    x = tf.nn.conv2d(x,W1,strides=[1,1,1,1],padding='VALID')\n",
    "    b1 = tf.Variable(tf.zeros(6),name='b1')\n",
    "    x = tf.nn.bias_add(x,b1)\n",
    "    print('layer 1 shape:',x.get_shape())\n",
    "    \n",
    "    #Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    # Pooling Input:28x28x6 output:14x14x6\n",
    "    x = tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1],padding='VALID')\n",
    "    layer1 = x\n",
    "    \n",
    "    #Layer2:Convolutiona 1 Output=10x10x16\n",
    "    W2 = tf.Variable(tf.truncated_normal(shape=(5,5,6,16),mean=mu,stddev=sigma),name='W2')\n",
    "    x = tf.nn.conv2d(x,W2,strides=[1,1,1,1],padding='VALID')\n",
    "    b2 = tf.Variable(tf.zeros(16),name='b2')\n",
    "    x = tf.nn.bias_add(x,b2)\n",
    "    \n",
    "    #Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    #Pooling Input=10x10x16 Output=5x5x16\n",
    "    x = tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1],padding='VALID')\n",
    "    layer2 = x\n",
    "    \n",
    "    #Layer3 Convolutional Output = 1x1x400\n",
    "    W3 = tf.Variable(tf.truncated_normal(shape=(5,5,16,400),mean=mu,stddev=sigma),name='W3')\n",
    "    x = tf.nn.conv2d(x,W3,strides=[1,1,1,1],padding='VALID')\n",
    "    b3 = tf.Variable(tf.zeros(400),name='b3')\n",
    "    x = tf.nn.bias_add(x,b3)\n",
    "    \n",
    "    #TODO:Activation\n",
    "    x = tf.nn.relu(x)\n",
    "    layers3 = x\n",
    "    \n",
    "    #TODO:Flateen Input:5x5x16 Output:400\n",
    "    layer2flat = flatten(layer2)\n",
    "    print('layer2flat shape:',layer2flat.get_shape())\n",
    "    \n",
    "    #Flatten x Input =1x1x400 Output = 400\n",
    "    xflat = flatten(x)\n",
    "    print('xflat shape:',xflat.get_shape())\n",
    "    \n",
    "    #Concat layer2flat and x Input=400+400 Output=800\n",
    "    x = tf.concat([xflat,layer2flat],1)\n",
    "    print('x shape:',x.get_shape())\n",
    "    \n",
    "    #Dropout\n",
    "    x = tf.nn.dropout(x,keep_prob)\n",
    "    \n",
    "    #Layer4:Fully Connected Input:800,Output:43\n",
    "    W4 = tf.Variable(tf.truncated_normal(shape=(800,43),mean=mu,stddev=sigma),name='W4')\n",
    "    b4 = tf.Variable(tf.zeros(43),name='b4')\n",
    "    logits = tf.add(tf.matmul(x,W4),b4)\n",
    "    \n",
    "    return logits\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "tf.reset_default_graph()\n",
    "x = tf.placeholder(tf.float32,(None,32,32,1))\n",
    "y = tf.placeholder(tf.int32,(None))\n",
    "keep_prob = tf.placeholder(tf.float32)\n",
    "one_hot_y = tf.one_hot(y,43)\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "layer 1 shape: (?, 28, 28, 6)\n",
      "layer2flat shape: (?, 400)\n",
      "xflat shape: (?, 400)\n",
      "x shape: (?, 800)\n"
     ]
    }
   ],
   "source": [
    "rate = 0.0009\n",
    "logits = LeNet2(x)\n",
    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits,labels=one_hot_y)\n",
    "loss_operation = tf.reduce_mean(cross_entropy)\n",
    "optimizer = tf.train.AdamOptimizer(learning_rate=rate)\n",
    "training_operation = optimizer.minimize(loss_operation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "correct_prediction = tf.equal(tf.argmax(logits,1),tf.argmax(one_hot_y,1))\n",
    "accuracy_operation = tf.reduce_mean(tf.cast(correct_prediction,tf.float32))\n",
    "saver = tf.train.Saver()\n",
    "def evaluate(X_data,y_data):\n",
    "    num_examples = len(X_data)\n",
    "    total_accuracy = 0\n",
    "    sess = tf.get_default_session()\n",
    "    for offset in range(0,num_examples,BATCH_SIZE):\n",
    "        batch_x,batch_y = X_data[offset:offset+BATCH_SIZE],y_data[offset:offset+BATCH_SIZE]\n",
    "        accuracy = sess.run(accuracy_operation,feed_dict={x:batch_x,y:batch_y,keep_prob:1.0})\n",
    "        total_accuracy+=(accuracy*len(batch_x))\n",
    "    return total_accuracy/num_examples\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training...\n",
      "EPOCH1...\n",
      "Validation Accuracy=0.870\n",
      "EPOCH2...\n",
      "Validation Accuracy=0.935\n",
      "EPOCH3...\n",
      "Validation Accuracy=0.957\n",
      "EPOCH4...\n",
      "Validation Accuracy=0.967\n",
      "EPOCH5...\n",
      "Validation Accuracy=0.975\n",
      "EPOCH6...\n",
      "Validation Accuracy=0.979\n",
      "EPOCH7...\n",
      "Validation Accuracy=0.981\n",
      "EPOCH8...\n",
      "Validation Accuracy=0.984\n",
      "EPOCH9...\n",
      "Validation Accuracy=0.985\n",
      "EPOCH10...\n",
      "Validation Accuracy=0.987\n",
      "EPOCH11...\n",
      "Validation Accuracy=0.987\n",
      "EPOCH12...\n",
      "Validation Accuracy=0.989\n",
      "EPOCH13...\n",
      "Validation Accuracy=0.988\n",
      "EPOCH14...\n",
      "Validation Accuracy=0.989\n",
      "EPOCH15...\n",
      "Validation Accuracy=0.988\n",
      "EPOCH16...\n",
      "Validation Accuracy=0.989\n",
      "EPOCH17...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH18...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH19...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH20...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH21...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH22...\n",
      "Validation Accuracy=0.989\n",
      "EPOCH23...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH24...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH25...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH26...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH27...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH28...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH29...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH30...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH31...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH32...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH33...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH34...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH35...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH36...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH37...\n",
      "Validation Accuracy=0.988\n",
      "EPOCH38...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH39...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH40...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH41...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH42...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH43...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH44...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH45...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH46...\n",
      "Validation Accuracy=0.993\n",
      "EPOCH47...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH48...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH49...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH50...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH51...\n",
      "Validation Accuracy=0.993\n",
      "EPOCH52...\n",
      "Validation Accuracy=0.990\n",
      "EPOCH53...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH54...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH55...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH56...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH57...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH58...\n",
      "Validation Accuracy=0.991\n",
      "EPOCH59...\n",
      "Validation Accuracy=0.992\n",
      "EPOCH60...\n",
      "Validation Accuracy=0.992\n",
      "Model saved\n"
     ]
    }
   ],
   "source": [
    "with tf.Session() as sess:\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    num_examples = len(X_train)\n",
    "    print('Training...')\n",
    "    for i in range(EPOCHS):\n",
    "        X_train,y_train = shuffle(X_train,y_train)\n",
    "        for offset in range(0,num_examples,BATCH_SIZE):\n",
    "            batch_x,batch_y = X_train[offset:offset+BATCH_SIZE],y_train[offset:offset+BATCH_SIZE]\n",
    "            sess.run(training_operation,feed_dict={x:batch_x,y:batch_y,keep_prob:0.5})\n",
    "        validation_accuracy = evaluate(X_validation,y_validation)\n",
    "        print('EPOCH{}...'.format(i+1))\n",
    "        print('Validation Accuracy={:.3f}'.format(validation_accuracy))\n",
    "    saver.save(sess,'./lenet')\n",
    "    print('Model saved')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from ./lenet\n",
      "Test Set Accuracy=0.947\n"
     ]
    }
   ],
   "source": [
    "with tf.Session() as sess:\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    saver2 = tf.train.import_meta_graph('./lenet.meta')\n",
    "    saver2.restore(sess,'./lenet')\n",
    "    test_accuracy = evaluate(X_test_normalized,y_test)\n",
    "    print('Test Set Accuracy={:.3f}'.format(test_accuracy))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test a model on New Images\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(32, 32, 3)\n",
      "(10, 32, 32, 1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.image as mpimg\n",
    "import glob\n",
    "import os\n",
    "\n",
    "IMG_HEIGHT = 32\n",
    "IMG_WIDTH = 32\n",
    "\n",
    "def get_list_files(my_dir,f_ext):\n",
    "    list_f = []\n",
    "    for file in os.listdir(my_dir):\n",
    "        if file.endswith('.'+f_ext):\n",
    "            list_f.append(file)\n",
    "    return list_f\n",
    "\n",
    "my_dir = 'extra'\n",
    "\n",
    "file_list = get_list_files(my_dir,'png')\n",
    "\n",
    "X_extra = np.zeros((len(file_list),IMG_HEIGHT,IMG_WIDTH,3),dtype='uint8')\n",
    "fig,axs = plt.subplots(5,2,figsize=(10,5))\n",
    "fig.subplots_adjust(hspace=.2,wspace=.001)\n",
    "axs = axs.ravel()\n",
    "for idx,file in enumerate(file_list):\n",
    "    img = cv2.imread(my_dir+'/'+file)\n",
    "    img = cv2.resize(img,(32,32))\n",
    "    img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)\n",
    "    axs[idx].imshow(img)\n",
    "    X_extra[idx] = img\n",
    "my_images = X_extra\n",
    "my_images_gry = np.sum(my_images/3,axis=3,keepdims=True)\n",
    "my_images_normalized = (my_images_gry-128)/128\n",
    "print(my_images_normalized.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read signnames\n",
    "with open('data/signnames.csv','r') as sign_name:\n",
    "    reader = csv.reader(sign_name)\n",
    "    sign_names = list(reader)\n",
    "\n",
    "sign_names = sign_names[1::]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:tensorflow]",
   "language": "python",
   "name": "conda-env-tensorflow-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
